wrab12/awesome-spatial-transcriptomics

A curated list of tools, foundation models, datasets and tutorials for spatial transcriptomics and single-cell analysis, ordered the way an analysis goes.

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updated Oct 12, 2026

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	I made a list of spatial transcriptomics tools ordered by analysis step (340 entries, every link and DOI checked). What's missing? (r/bioinformatics) When I got into spatial transcriptomics, it was hard to tell which tool fits which step, so I put together the list I wish I'd had: [https://github.com/wrab12/awesome-spatial-transcriptomics](https://github.com/wrab12/awesome-spatial-transcriptomics) There are already good lists…	8	Oct 8, 2026

README

Awesome Spatial Transcriptomics

A curated list of tools, foundation models, datasets, tutorials and papers for spatial transcriptomics and the single-cell methods it builds on, ordered the way an analysis actually goes.

Spatial transcriptomics measures gene expression while keeping track of where each cell sits in the tissue. New platforms appear every year, there are hundreds of methods, and foundation models have joined in. This list aims to make the field easy to navigate:

Ordered like an analysis. Sections run from technologies and preprocessing to domains, deconvolution, alignment, cell–cell communication and spatiotemporal modeling.
Spatial and single-cell together. Spatial analysis relies on single-cell tools for annotation, integration and trajectories, so both are covered.
Up to date. Includes work from 2023–2026: tools for subcellular platforms such as Visium HD and Xenium, foundation models, LLM agents and recent benchmarks.
Checked. Every repository and paper link was verified when added, and the star badges update automatically.
A place to start. If you are new to the field, begin with the free books, courses and reviews in Start Here.

Within each table, tools are sorted by GitHub stars. Stars measure popularity, not quality, so check the benchmarks before picking a method.

Start Here
Spatial Technologies
Spatial Transcriptomics Analysis
Single-Cell Foundations
AI & Foundation Models
Benchmarks & Evaluation
Data
- Atlases, data portals & databases
- Simulation
Related lists
Contributing

🧭 Start Here

Best-practice guides & books

Free books that walk through a complete analysis.

Single-cell Best Practices – Open Jupyter Book on scverse-based analysis of single-cell and spatial omics, from preprocessing to multimodal integration. Nature Reviews Genetics 2023
Orchestrating Single-Cell Analysis with Bioconductor (OSCA) – Bioconductor online book covering scRNA-seq analysis in R, from data import and QC to multi-sample workflows. Nature Methods 2020
Orchestrating Spatial Transcriptomics Analysis with Bioconductor (OSTA) – Bioconductor online book with tested R workflows for sequencing- and imaging-based spatial transcriptomics data. bioRxiv 2025 (preprint)
A Practical Guide to Spatial Transcriptomics: Lessons from over 1000 Samples – Practical guide for Visium, Visium HD and Xenium projects: experimental design, tissue handling, sequencing and analysis. Trends in Biotechnology 2026

Courses & hands-on tutorials

Notebooks and vignettes you can run end to end.

scverse tutorials (Scanpy and ecosystem) – Curated hub of maintained Python tutorials for Scanpy, AnnData, muon, scvi-tools, Squidpy, SpatialData and other scverse packages. Nature Biotechnology 2023
scvi-tools tutorials – Notebooks for scvi-tools deep generative models: integration, reference mapping, multimodal analysis and spatial deconvolution. Nature Biotechnology 2022
Squidpy tutorials – Spatial analysis tutorials (graphs, neighborhood enrichment, spatial statistics, image features) for Visium, Xenium, MERFISH, Slide-seq and more. Nature Methods 2022
SpatialData tutorials – Notebooks for loading, aligning, querying and visualizing multi-technology spatial omics data with the SpatialData framework. Nature Methods 2025
Seurat vignettes (incl. spatial) – Official R vignettes from guided PBMC clustering to integration, multimodal analysis and sequencing- and imaging-based spatial data. Nature Biotechnology 2024
HBC Introduction to single-cell RNA-seq – Harvard Chan Bioinformatics Core workshop: design, QC, normalization, integration, clustering and marker genes with Seurat or Scanpy.
HBC Introduction to Spatial Transcriptomics – Harvard Chan workshop on Visium HD in Seurat: QC, clustering, RCTD deconvolution, BANKSY domains, Moran's I, CellChat.
Analysis of single cell RNA-seq data (Sanger / Hemberg lab course) – Classic Cambridge/Sanger course book: scRNA-seq technologies, raw data processing, QC, normalization, clustering and integration in R.
Galaxy Training Network: Single Cell – Galaxy Training Network tutorials and learning pathways for single-cell analysis, GUI or notebook based, including spatial transcriptomics. GigaScience 2020
Voyager tutorials – Vignettes applying geospatial statistics (Moran's I, local indicators, Lee's L) to spatial omics via SpatialFeatureExperiment. bioRxiv 2023 (preprint)
Giotto Suite tutorials – Technology-agnostic spatial omics tutorials in R: Visium/HD, Xenium, CosMx, MERFISH, CODEX; domains, deconvolution, multi-sample integration. Nature Methods 2025
10x Genomics Analysis Guides – Vendor tutorials and method overviews for Chromium, Visium/Visium HD and Xenium data, with Colab-ready notebooks.
NBIS single-cell RNA-seq workshop – Regularly updated NBIS course with parallel Seurat, Bioconductor and Scanpy labs from QC to cell typing and trajectories.
SIB Single Cell Transcriptomics course – SIB three-day course material in R (Seurat, Bioconductor): QC, integration, clustering, annotation, DE, enrichment and trajectories.

Key reviews

Reviews worth reading before choosing methods.

Spatial architecture of development and disease (Lázár & Lundeberg) – Recent review of how spatial omics reveals tissue organization in development and disease. Nature Reviews Genetics 2026
Towards multimodal foundation models in molecular cell biology (Cui et al.) – Perspective on foundation models pretrained across genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial profiling. Nature 2025
Transformers in single-cell omics: a review and new perspectives (Szałata et al.) – Explains transformer architectures and reviews their single-cell applications, including foundation models, with limitations and future directions. Nature Methods 2024
How to build the virtual cell with artificial intelligence: Priorities and opportunities (Bunne et al.) – Perspective on AI virtual cells: multiscale, multimodal neural network models that represent and simulate molecules, cells and tissues. Cell 2024
Unlocking the power of spatial omics with AI (Coleman, Schroeder & Li) – Short Comment on how AI methods can help analyze and integrate complex spatial omics datasets. Nature Methods 2024
Best practices for single-cell analysis across modalities (Heumos et al.) – Benchmark-based best-practice workflows for single-cell RNA, chromatin, surface protein, immune repertoire and spatial data. Nature Reviews Genetics 2023
Methods and applications for single-cell and spatial multi-omics (Vandereyken et al.) – Reviews single-cell and spatial multi-omics technologies, the computational integration strategies they need, and their applications. Nature Reviews Genetics 2023
The expanding vistas of spatial transcriptomics (Tian, Chen & Macosko) – Reviews how spatial transcriptomics technologies evolved in sensitivity, multiplexing and throughput, and what they enable. Nature Biotechnology 2023
The dawn of spatial omics (Bressan, Battistoni & Hannon) – Systematic catalog of spatial omics technology families, their principles and limitations, and the field's main challenges. Science 2023
Museum of spatial transcriptomics (Moses & Pachter) – Curated history of spatial transcriptomics since 1987, with trend analysis of technologies, tissues and computational methods. Nature Methods 2022
Spatial components of molecular tissue biology (Palla et al.) – Groups spatial transcriptomics and proteomics analysis problems and algorithms by tissue length scale, outlining open computational challenges. Nature Biotechnology 2022
Computational principles and challenges in single-cell data integration (Argelaguet et al.) – Defines horizontal, vertical and diagonal integration of single-cell data and reviews methods, assumptions and open challenges. Nature Biotechnology 2021
Deciphering cell–cell interactions and communication from gene expression (Armingol et al.) – Reviews how cell–cell communication is inferred from transcriptomic data, mainly ligand–receptor approaches, and the tools used. Nature Reviews Genetics 2021
Method of the Year: spatially resolved transcriptomics (Marx) – Nature Methods feature naming spatially resolved transcriptomics Method of the Year 2020, surveying its technologies and prospects. Nature Methods 2021
Exploring tissue architecture using spatial transcriptomics (Rao et al.) – Reviews sequencing- and imaging-based spatial transcriptomics technologies and the range of analyses applied to their data. Nature 2021
Eleven grand challenges in single-cell data science (Lähnemann et al.) – Community overview of major open computational challenges in single-cell data science and the research needed to address them. Genome Biology 2020
Current best practices in single-cell RNA-seq analysis: a tutorial (Luecken & Theis) – Step-by-step tutorial and recommendations for standard scRNA-seq analysis, from QC and normalization to clustering and trajectories. Molecular Systems Biology 2019

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🔬 Spatial Technologies

Spatial technologies

Landmark platforms and their method papers, grouped by how they measure and sorted by year.

Sequencing-based (spatially barcoded capture, then sequencing)

Technology	Description	Paper
Spatial Transcriptomics (ST)	Barcoded oligo-dT spot arrays capture mRNA from tissue sections for genome-wide spatial profiling; foundational array method (100 µm spots).	Science 2016
Slide-seq / Slide-seqV2	Tissue placed on a monolayer of DNA-barcoded 10 µm beads whose positions are decoded by in situ sequencing.	Science 2019
HDST	High-definition spatial transcriptomics: RNA captured on a dense, spatially barcoded bead array at 2 µm resolution.	Nature Methods 2019
DBiT-seq	Microfluidic deterministic barcoding: crossed channel sets create a 2D pixel grid for co-profiling mRNA and proteins in tissue.	Cell 2020
Seq-Scope	Repurposes Illumina flow-cell clusters as barcoded capture arrays; pixels ~0.5–0.8 µm apart for submicrometer spatial transcriptomics.	Cell 2021
Stereo-seq	DNA nanoball-patterned arrays give nanoscale capture spots over centimeter-scale areas; debuted with a mouse organogenesis atlas (MOSTA).	Cell 2022
Slide-tags	Spatial barcodes from a bead array tag nuclei in intact tissue, enabling spatially resolved single-nucleus RNA, ATAC and multimodal profiling.	Nature 2024
Open-ST	Open-source, low-cost sequencing-based method on patterned Illumina flow cells with subcellular resolution and 3D virtual tissue reconstruction.	Cell 2024
Visium / Visium HD (10x Genomics)	10x Genomics capture arrays: Visium (55 µm spots) and Visium HD (gapless 2 µm barcoded squares, usually binned).	Nature Genetics 2025

Imaging-based (in situ hybridization or sequencing, read by microscopy)

Technology	Description	Paper
MERFISH	Multiplexed error-robust FISH: combinatorial binary barcodes read over sequential imaging rounds profile hundreds to thousands of RNAs.	Science 2015
STARmap / STARmap PLUS	In situ sequencing of hydrogel-embedded intact tissue in 3D; STARmap PLUS adds protein co-detection at subcellular resolution.	Science 2018
osmFISH	Cyclic, non-barcoded single-molecule FISH (ouroboros smFISH) mapping cell-type markers across mouse somatosensory cortex.	Nature Methods 2018
seqFISH+	Sequential FISH with 60 pseudocolors images ~10,000 genes at super-resolution in single cells within tissue.	Nature 2019
CosMx SMI	Spatial molecular imaging: cyclic hybridization of fluorescent barcodes measured 980 RNAs and 108 proteins in FFPE tissue.	Nature Biotechnology 2022
Xenium (10x Genomics)	10x in situ platform: padlock probes, rolling-circle amplification and cyclic imaging detect targeted gene panels at subcellular resolution.	Nature Communications 2023
EEL FISH	Electrophoretically transfers RNA from tissue onto a capture surface, then decodes it by multiplexed smFISH for fast imaging.	Nature Biotechnology 2023

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📍 Spatial Transcriptomics Analysis

Spatial frameworks

General-purpose toolkits and data structures for spatial omics.

Tool	Description	Lang	Paper
Seurat (spatial vignettes)	Seurat workflows for sequencing- and imaging-based spatial data (Visium, Visium HD, Slide-seq, Xenium, CosMx, MERFISH).	R	Nature Biotechnology 2024
Squidpy	scverse toolkit for spatial omics: spatial graphs, neighborhood enrichment, co-occurrence, ligand–receptor analysis and image features.	Python	Nature Methods 2022
SpatialData	Universal data framework (Zarr/OME-NGFF) unifying images, labels, points, shapes and tables across spatial omics technologies.	Python	Nature Methods 2025
Giotto Suite	Modular R ecosystem for technology-agnostic, multiscale spatial multi-omics analysis, integration and visualization.	R	Nature Methods 2025
stLearn	Integrates histology images, spatial coordinates and expression for normalization, clustering, spatial trajectories and cell–cell interactions.	Python	Nature Communications 2023
SPATA2	R framework for spatial transcriptomics emphasizing histology-guided analyses such as spatial gradient screening along tissue axes.	R	Nature Communications 2024
Voyager / SpatialFeatureExperiment	Brings geospatial exploratory statistics (e.g., Moran's I, local indicators) to spatial omics on SpatialFeatureExperiment geometries.	R	bioRxiv 2023 (preprint)
semla	Seurat-compatible R toolkit for Visium/ST analysis, visualization, image alignment and spatial utilities; successor of STUtility.	R	Bioinformatics 2023
SpatialExperiment	Bioconductor S4 class extending SingleCellExperiment with spatial coordinates and images; core data structure for R spatial tools.	R	Bioinformatics 2022

Cell segmentation & preprocessing

From images and transcripts or bins to cells.

Tool	Description	Lang	Paper
Cellpose	Generalist deep-learning cell and nucleus segmentation predicting spatial flow fields; supports human-in-the-loop training and 3D.	Python	Nature Methods 2021
StarDist	Deep-learning object detection with star-convex polygons; accurate nucleus segmentation in crowded 2D and 3D images.	Python	MICCAI 2018 (LNCS)
Mesmer (DeepCell)	Deep-learning whole-cell and nuclear segmentation for multiplexed tissue images, trained on the TissueNet dataset.	Python	Nature Biotechnology 2022
Sopa	Technology-invariant, scalable SpatialData-based pipeline for segmentation, aggregation and annotation across imaging-based spatial omics and Visium HD.	Python	Nature Communications 2024
Baysor	Bayesian segmentation of imaging-based ST from molecule positions and gene composition, optionally guided by a prior segmentation.	C++	Nature Biotechnology 2022
Proseg	Probabilistic segmentation that simulates cell shapes (cellular Potts model) to best explain transcript positions; fast, unsupervised.	Rust	Nature Methods 2025
bin2cell	Reconstructs cells from Visium HD 2 µm bins using StarDist nuclei from H&E and expression images plus label expansion.	Python	Bioinformatics 2024
ENACT	End-to-end Visium HD pipeline: cell segmentation, bin-to-cell assignment and cell-type annotation across whole tissue sections.	Python	Bioinformatics 2025
Segger	Graph neural network that assigns transcripts to cells via link prediction on a heterogeneous transcript–cell graph.	Python	bioRxiv 2025 (preprint)
Space Ranger	Official 10x pipelines for Visium/Visium HD: alignment, image registration, tissue detection, binning; v4+ adds nucleus-based cell segmentation.	Rust

Spatially variable genes

Genes whose expression follows tissue structure.

Tool	Description	Lang	Paper
SpatialDE	Gaussian-process regression tests each gene for spatial variance; automatic expression histology groups genes into spatial patterns.	Python	Nature Methods 2018
Hotspot	Local autocorrelation on a cell–cell neighbor graph (spatial or transcriptional) to find informative genes and gene modules.	Python	Cell Systems 2021
MERINGUE	Spatial auto- and cross-correlation on Voronoi-based neighbor graphs; robust to non-uniform cell densities.	R	Genome Research 2021
SPARK / SPARK-X	SPARK: spatial generalized linear mixed model on raw counts; SPARK-X: fast non-parametric covariance test for large datasets.	R	Nature Methods 2020
nnSVG	Scalable SVG detection using nearest-neighbor Gaussian processes with gene-specific length scales; linear in number of spots.	R	Nature Communications 2023
Celina	Spatially varying coefficient model detecting cell type-specific spatially variable genes in spot- or single-cell-resolution data.	R	Nature Communications 2025
sepal	Simulates diffusion of each gene's expression; genes slow to reach homogeneity are ranked as spatially structured.	Python	Bioinformatics 2021
SpaGFT	Graph Fourier transform of expression on spatial graphs identifies SVGs and tissue modules; enhances downstream ML tasks.	Python	Nature Communications 2024

Spatial domains & clustering

Tissue regions from expression plus spatial context.

Tool	Description	Lang	Paper
SpaGCN	Graph convolutional network combining expression, location and histology to find spatial domains and domain-specific SVGs.	Python	Nature Methods 2021
CellCharter	Aggregates features from multi-hop spatial neighbors and clusters with Gaussian mixtures to find niches across samples.	Python	Nature Genetics 2024
BayesSpace	Bayesian clustering with a Markov random field prior for spatial domains; enhances Visium/ST to sub-spot resolution.	R	Nature Biotechnology 2021
BANKSY	Augments each cell's expression with neighborhood mean and gradient features, unifying cell typing and domain segmentation.	R	Nature Genetics 2024
GraphST	Graph self-supervised contrastive learning for spatial clustering, multi-section integration and scRNA-seq-to-spatial cell-type deconvolution.	Python	Nature Communications 2023
DeepST	Combines histology morphology features, expression and location with graph and denoising autoencoders to identify spatial domains.	Python	Nucleic Acids Research 2022
SEDR	Masked graph autoencoder plus deep autoencoder learns spatial embeddings for clustering, denoising and batch integration.	Python	Genome Medicine 2024
STAGATE	Graph attention autoencoder learning spatially aware embeddings for domain identification and denoising, including 3D tissue.	Python	Nature Communications 2022
spaVAE	Gaussian-process VAE capturing spatial correlation for clustering, denoising, imputation and resolution enhancement; ATAC/multi-omics variants.	Python	Nature Methods 2024
BASS	Bayesian hierarchical model jointly performing cell-type clustering and spatial domain detection across multiple tissue sections.	R	Genome Biology 2022
SpaceFlow	Spatially regularized deep graph network learning embeddings for domains and pseudo-spatiotemporal maps of tissues.	Python	Nature Communications 2022

Deconvolution & single-cell mapping

Cell-type composition of spots and mapping of single cells onto tissue.

Tool	Description	Lang	Paper
DestVI (scvi-tools)	Conditional deep generative model inferring cell-type proportions and continuous within-type state variation per spot.	Python	Nature Biotechnology 2022
RCTD (spacexr)	Supervised Poisson model with platform-effect normalization decomposing spots into cell types; spacexr also includes C-SIDE DE testing.	R	Nature Biotechnology 2022
cell2location	Hierarchical Bayesian model mapping fine-grained cell types from scRNA-seq references to spatial data as absolute abundances.	Python	Nature Biotechnology 2022
Tangram	Deep-learning alignment of scRNA-seq profiles onto spatial data to map cells, project genes and deconvolve spots.	Python	Nature Methods 2021
SPOTlight	Seeded NMF regression using cell-type marker genes from scRNA-seq to deconvolve spatial spots.	R	Nucleic Acids Research 2021
STdeconvolve	Reference-free deconvolution using latent Dirichlet allocation topic modeling of multicellular spatial pixels.	R	Nature Communications 2022
CytoSPACE	Assigns individual scRNA-seq cells to spots by convex optimization, respecting estimated cell numbers per spot.	Python	Nature Biotechnology 2023
CARD	Deconvolution with a conditional autoregressive prior on spatial composition; builds refined-resolution maps; reference-free mode available.	R	Nature Biotechnology 2022
CellTrek	Maps single cells to tissue coordinates via scRNA-seq–spatial co-embedding and random-forest similarity learning.	R	Nature Biotechnology 2022
stereoscope	Negative-binomial probabilistic model inferring per-spot cell-type proportions from a single-cell reference.	Python	Communications Biology 2020
Redeconve	Regularized non-negative regression using single cells as reference, deconvolving spots into thousands of fine cell states.	R	Nature Communications 2023

Alignment, integration & 3D reconstruction

Registering slices, integrating samples and building 3D tissue.

Tool	Description	Lang	Paper
Spateo	3D spatiotemporal framework: slice alignment, whole-embryo 3D reconstruction, morphometric vector fields, spatial domains and cell–cell interactions.	Python	Cell 2024
STalign	Diffeomorphic metric mapping (LDDMM) aligns single-cell-resolution ST slices to each other or to 3D reference atlases.	Python	Nature Communications 2023
PASTE	Fused Gromov–Wasserstein optimal transport for pairwise alignment of adjacent ST slices and integration into a consensus center slice.	Python	Nature Methods 2022
SLAT	Graph neural network with adversarial matching aligns heterogeneous single-cell spatial slices across technologies and modalities.	Python	Nature Communications 2023
STitch3D	Jointly models multiple 2D slices with an scRNA-seq reference to reconstruct 3D tissue regions and cell-type distributions.	Python	Nature Machine Intelligence 2023
SPACEL	Deep-learning toolkit: Spoint deconvolution, Splane multi-slice domains, and Scube alignment and stacking of consecutive slices into 3D.	Python	Nature Communications 2023
STAligner	Graph attention autoencoder with spot-triplet loss integrates slices across conditions, technologies and developmental stages; supports 3D alignment.	Python	Nature Computational Science 2023
PASTE2	Partial fused Gromov–Wasserstein OT aligns partially overlapping slices, optionally using histology, enabling 3D stacking.	Python	Genome Research 2023
CAST	Self-supervised graph embeddings plus rigid and free-form alignment to search and match spatial samples at single-cell resolution.	Python	Nature Methods 2024
GPSA	Deep Gaussian process model that maps multiple spatial genomics and histology slices into a common coordinate system.	Python	Nature Methods 2023
SpatialZ	Generates virtual single-cell slices between measured sections to build dense 3D cell atlases from planar ST data.	Python	Nature Methods 2026
SANTO	Coarse-to-fine alignment and stitching of partially overlapping spatial omics slices, in 2D or 3D and across omics types.	Python	Nature Communications 2024

Cell–cell communication & niches

Spatially aware signaling, interaction and niche analysis.

Tool	Description	Lang	Paper
LIANA+	All-in-one cell–cell communication framework unifying many ligand–receptor methods, with spatially informed bivariate metrics and multi-view (MISTy) modeling.	Python	Nature Cell Biology 2024
COMMOT	Collective optimal transport infers ligand–receptor signaling and its spatial direction, accounting for competition among ligands and receptors.	Python	Nature Methods 2023
NicheCompass	Interpretable graph deep learning using prior interaction-pathway knowledge to learn signaling-aware embeddings and characterize cell niches at scale.	Python	Nature Genetics 2025
NCEM	Node-centric expression models (linear to graph neural networks) predict a cell's expression from its spatial neighbors to infer communication.	Python	Nature Biotechnology 2023
FlowSig	Graphical causal modeling of intercellular flows linking incoming signals, intracellular gene modules and outgoing signals.	Python	Nature Methods 2024
SpaTalk	Knowledge-graph-based inference of ligand–receptor–target signaling between spatially proximal cells; deconvolves spot data into single cells.	R	Nature Communications 2022
MISTy (mistyR)	Explainable multiview machine learning that dissects intracellular and neighborhood (juxta-/para-view) relationships among markers in spatial omics.	R	Genome Biology 2022
CellNEST	Graph attention model that detects cell–cell communication and multi-hop relay networks from spatial transcriptomics.	Python	Nature Methods 2025
SpaOTsc	Structured optimal transport maps scRNA-seq cells to spatial locations and infers spatially constrained cell–cell signaling.	Python	Nature Communications 2020
SpatialDM	Bivariate Moran's statistic with an analytical null detects spatially co-expressed ligand–receptor pairs and local interaction hotspots, at scale.	Python	Nature Communications 2023

Super-resolution, imputation & histology-to-expression

Higher resolution, more genes, or expression predicted from H&E.

Tool	Description	Lang	Paper
gimVI (scvi-tools)	Joint generative (VAE) model of scRNA-seq and spatial data that imputes genes missing from targeted spatial panels.	Python	arXiv 2019 (preprint)
iStar	Combines hierarchical histology image features with spot-level ST to predict near-single-cell super-resolution expression and annotate tissue.	Python	Nature Biotechnology 2024
ST-Net	Early CNN model predicting spatially resolved expression of hundreds of genes from breast cancer H&E image patches.	Python	Nature Biomedical Engineering 2020
BLEEP	Bi-modal contrastive learning aligns H&E patch and expression embeddings, then predicts expression by retrieving similar reference spots.	Python	NeurIPS 2023
SpatialScope	Deep generative model that brings spot-level spatial data to single-cell resolution and imputes transcriptome-wide expression.	Python	Nature Communications 2023
XFuse	Bayesian deep generative model fusing histology and spot-level ST to infer super-resolved expression, including in unmeasured tissue.	Python	Nature Biotechnology 2022
GHIST	Multitask deep learning predicts single-cell-resolution spatial expression from H&E, trained on subcellular-resolution ST data.	Python	Nature Methods 2025
TESLA	Integrates histology with spot-level ST to impute pixel-level expression and annotate tumor and immune cell regions.	Python	Cell Systems 2023
ENVI (scENVI)	Variational model integrating scRNA-seq with spatial data to impute unimaged genes and infer COVET niche context for dissociated cells.	Python	Nature Biotechnology 2025
iSCALE	Predicts super-resolution expression for tissues larger than ST capture areas, using a large H&E image and several ST captures.	Python	Nature Methods 2025
TISSUE	Calibrated uncertainty estimates for imputed spatial gene expression, enabling more reliable downstream analyses.	Python	Nature Methods 2024
SpaGE	Aligns scRNA-seq and spatial data with domain adaptation (PRECISE), then predicts unmeasured genes by k-nearest-neighbor regression.	Python	Nucleic Acids Research 2020

Spatiotemporal & generative modeling

Dynamics across time points and generation of spatial data.

Tool	Description	Lang	Paper
moscot	Scalable optimal-transport framework mapping cells across time, space and modalities, including spatial alignment/mapping and spatiotemporal problems.	Python	Nature 2025
stVCR	Reconstructs continuous single-cell differentiation, proliferation, migration and slice alignment from time-series ST via unbalanced dynamical OT.	Python	Nature Methods 2026
Wasserstein Flow Matching (WFM)	Flow matching over families of distributions (Gaussians, point clouds); generates high-dimensional cellular microenvironments (niches) from ST data.	Python	ICML 2025
spaTrack	Optimal-transport trajectory inference combining expression and spatial distance, within single ST slices and across time-series slices.	Python	Cell Systems 2025
STORIES	Learns a differentiation potential (cell-fate landscape) from spatial transcriptomics time courses using fused Gromov–Wasserstein optimal transport.	Python	Nature Methods 2026
NicheFlow	Flow-matching generative model predicting how cellular microenvironments (cell states plus coordinates) evolve across time-resolved ST slices.	Python	NeurIPS 2025
STT (spatial transition tensor)	Learns a 4D transition tensor from mRNA splicing and spatial data to map multistable attractors and spatial state transitions.	Python	Nature Methods 2024
DeST-OT	Semi-relaxed optimal transport aligns ST slices from developmental timepoints, inferring per-spot growth and migration.	Python	Cell Systems 2025
GenOT	Graph contrastive learning plus fused Gromov–Wasserstein barycenter interpolation generates intermediate slices and integrates cross-platform ST data. (Disclosure: by the list maintainer.)	Python	Genome Biology 2026

Visualization & interactive exploration

Viewers for large spatial and single-cell datasets.

Tool	Description	Lang	Paper
CZ CELLxGENE (Annotate / Explorer)	No-code interactive explorer for single-cell datasets: embeddings, gene expression, subsetting and annotation.	Python/JS	Nucleic Acids Research 2025
Vitessce	Web framework for coordinated multiview visualization of multimodal and spatial single-cell data; usable from Jupyter and R.	JS/TS	Nature Methods 2025
iSEE	Interactive Shiny explorer for SummarizedExperiment/SingleCellExperiment objects with linked, customizable panels and reproducible code export.	R	F1000Research 2018
Cirrocumulus	Scalable web viewer for embeddings, dot plots, heatmaps and collaborative cell annotation of h5ad, Seurat, 10x and spatial data.	Python/JS	Nature Methods 2020
napari-spatialdata	napari plugin to interactively view and annotate SpatialData objects: images, labels, points, shapes and tables.	Python	Nature Methods 2025
spatialdata-plot	Static matplotlib-based plotting of SpatialData images, labels, points and shapes through a chainable API.	Python	Nature Methods 2025
TissUUmaps	Browser-based viewer, hosted or local, for exploring millions of spatial data points over tissue images and sharing views.	JS/TS	Heliyon 2023
ShinyCell / ShinyCell2	R packages that turn single-cell objects (ShinyCell2 also spatial, scATAC, CITE-seq) into shareable Shiny web apps.	R	Bioinformatics 2021
WebAtlas	Pipeline that turns single-cell and spatial datasets into interactive, Vitessce-based web atlases.	Python	Nature Methods 2025
Xenium Explorer (10x Genomics)	Desktop app for interactively exploring Xenium in situ data: transcripts, cell segmentation, images and clusters.	Desktop app
Loupe Browser (10x Genomics)	Desktop app for interactive exploration of 10x Chromium single-cell and Visium/Visium HD spatial data.	Desktop app

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🧬 Single-Cell Foundations

Single-cell frameworks & data structures

The ecosystems most spatial tools build on.

Tool	Description	Lang	Paper
Seurat	Widely used R toolkit for single-cell QC, normalization, clustering, differential expression, integration, multimodal and spatial analysis.	R	Nature Biotechnology 2024
Scanpy	Scalable Python toolkit for single-cell analysis on AnnData: preprocessing, clustering, embeddings, differential expression, PAGA and plotting.	Python	Genome Biology 2018
scvi-tools	PyTorch library of probabilistic deep generative models (scVI, scANVI, totalVI and more) for integration, annotation and multimodal analysis.	Python	Nature Biotechnology 2022
AnnData	Python annotated data matrix (cells × features with metadata, layers, embeddings); defines the .h5ad/zarr formats used across scverse.	Python	Journal of Open Source Software 2024
sceasy	Converts between Seurat, SingleCellExperiment, AnnData and Loom objects from R, using reticulate and Python anndata/loompy.	R
rapids-singlecell	GPU-accelerated, largely Scanpy-compatible single-cell analysis on AnnData using CuPy/RAPIDS; includes selected Squidpy, decoupler and pertpy functions.	Python	arXiv 2026 (preprint)
BPCells	Bitpacked, disk-backed sparse matrices and streaming algorithms for scalable scRNA-seq and scATAC-seq analysis in R; usable within Seurat v5.	R/C++	bioRxiv 2025 (preprint)
MuData / muon	MuData container (.h5mu) for multimodal data plus muon toolkit for ATAC, protein and multi-omic integration (MOFA+, WNN).	Python	Genome Biology 2022
zellkonverter	Converts between AnnData/.h5ad files and Bioconductor SingleCellExperiment objects, using a managed Python environment (basilisk) or native R reader.	R
anndataR	Native R reading/writing of .h5ad and zarr AnnData files, with conversion to SingleCellExperiment and Seurat; no Python needed.	R	Bioinformatics 2026
scater	Bioconductor toolkit for single-cell QC, visualization and dimensionality reduction on SingleCellExperiment objects.	R	Bioinformatics 2017
SingleCellExperiment	Core Bioconductor S4 container for single-cell data, used by scater, scran, batchelor and most Bioconductor single-cell packages.	R	Nature Methods 2020

Raw data processing

From reads to count matrices.

Tool	Description	Lang	Paper
STARsolo	Single-cell mode of the STAR aligner; Cell Ranger-like barcode/UMI counting for many protocols, with spliced/unspliced (velocity) output.	C++	bioRxiv 2021 (preprint)
Cell Ranger	Official 10x Genomics pipelines for Chromium data: alignment, barcode/UMI counting, cell calling, Feature Barcode and V(D)J analysis.	Rust	Nature Communications 2017
nf-core/scrnaseq	Nextflow best-practice pipeline for 10x scRNA-seq: simpleaf, STARsolo, kallisto\|bustools or Cell Ranger, plus CellBender filtering and MultiQC.	Nextflow
zUMIs	Pipeline for UMI and plate-based scRNA-seq (including Smart-seq3): STAR mapping, exon/intron counting, barcode detection and UMI collapsing.	R	GigaScience 2018
alevin-fry / simpleaf	Fast, memory-frugal scRNA-seq quantification from piscem/salmon mappings, with spliced/unspliced/ambiguous (USA) counting; simpleaf wraps the workflow.	Rust	Nature Methods 2022
kallisto \| bustools (kb-python)	Wraps kallisto pseudoalignment and bustools into one-command scRNA-seq preprocessing; supports many technologies, single-nucleus and RNA-velocity workflows.	Python	Nature Biotechnology 2021

Quality control

Ambient RNA, doublets and low-quality cells.

Tool	Description	Lang	Paper
DoubletFinder	Seurat-based doublet detection comparing each cell's neighborhood with simulated artificial doublets (pANN score).	R	Cell Systems 2019
CellBender	Deep generative model that removes ambient RNA and barcode-swapping background from raw droplet count matrices and calls cells.	Python	Nature Methods 2023
SoupX	Estimates the ambient-RNA ('soup') profile from empty droplets and removes the contamination from each cell's counts.	R	GigaScience 2020
scDblFinder	Fast doublet detection training gradient-boosted trees on real cells versus simulated doublets; handles multiple samples and scATAC-seq.	R	F1000Research 2022
Scrublet	Python doublet detection scoring each cell by k-NN similarity to simulated doublets built from random pairs of observed cells.	Python	Cell Systems 2019
Solo	Semi-supervised scVI-based classifier separating singlets from simulated doublets. Maintained in scvi-tools (original repo archived).	Python	Cell Systems 2020
DecontX	Bayesian model that estimates and removes per-cell ambient RNA contamination from cluster-level profiles; no empty droplets required.	R	Genome Biology 2020
DropletUtils (EmptyDrops)	Bioconductor utilities for droplet data: EmptyDrops cell calling, barcode-rank knee detection, swapped-barcode removal and 10x I/O.	R	Genome Biology 2019
miQC	Mixture model of mitochondrial fraction and genes detected that sets adaptive, data-driven cell-filtering thresholds instead of fixed cutoffs.	R	PLOS Computational Biology 2021

Normalization & feature selection

Tool	Description	Lang	Paper
sctransform	Regularized negative binomial regression; Pearson residuals give normalized, variance-stabilized UMI data (Seurat's SCTransform).	R	Genome Biology 2019
scran	Pooling-based (deconvolution) size factors for normalization, plus variance modeling for HVG selection and marker detection.	R	Genome Biology 2016
Analytic Pearson residuals	Closed-form Pearson residuals from a fixed-overdispersion negative binomial model for UMI normalization and HVG selection; implemented in Scanpy.	Python	Genome Biology 2021
Feature selection benchmark (Zappia et al.)	Benchmark of 20+ feature-selection methods for scRNA-seq integration and query mapping; finds highly variable gene selection effective.	Python/R	Nature Methods 2025
scry	Multinomial-model tools: binomial-deviance feature selection, null residuals and GLM-PCA dimensionality reduction on raw UMI counts.	R	Genome Biology 2019
transformGamPoi	Variance-stabilizing transformations for UMI counts: acosh, shifted log, Pearson and randomized-quantile residuals.	R	Nature Methods 2023

Integration, batch correction & reference mapping

Tool	Description	Lang	Paper
scVI	Variational autoencoder for raw counts conditioned on batch; its latent space is used for integration, normalization and differential expression. Part of scvi-tools.	Python	Nature Methods 2018
scANVI	Semi-supervised scVI extension that uses available cell-type labels for label-aware integration and label transfer to unannotated cells. Part of scvi-tools.	Python	Molecular Systems Biology 2021
sysVI	Conditional VAE with VampPrior and cycle-consistency for integrating systems with substantial batch effects (species, organoid vs tissue, cells vs nuclei). Part of scvi-tools.	Python	BMC Genomics 2025
Harmony	Iterative soft clustering in PCA space with cluster-specific linear corrections that remove dataset effects; fast and scalable.	R	Nature Methods 2019
LIGER (rliger)	Integrative non-negative matrix factorization (iNMF) learning shared and dataset-specific factors across samples, modalities and species.	R	Cell 2019
scArches	Transfer-learning 'architecture surgery' that maps query datasets onto pretrained reference models (e.g., scVI, scANVI) without sharing raw data.	Python	Nature Biotechnology 2022
scPoli	Generative model that learns sample embeddings and cell-type prototypes for population-level integration, reference mapping and label transfer. Part of scArches.	Python	Nature Methods 2023
Scanorama	Panorama-stitching integration that finds mutual nearest neighbors across all dataset pairs; handles heterogeneous collections with partially shared cell types.	Python	Nature Biotechnology 2019
BBKNN	Batch-balanced k-nearest-neighbor graph built per batch; fast graph-level correction feeding Scanpy clustering and UMAP.	Python	Bioinformatics 2020
Symphony	Compresses a Harmony-integrated reference so new query cells can be mapped and annotated in seconds without re-integration.	R	Nature Communications 2021
batchelor (MNN / fastMNN)	Bioconductor batch correction with mutual nearest neighbors (MNN, fastMNN) and related methods for SingleCellExperiment objects.	R	Nature Biotechnology 2018

Dimensionality reduction, clustering & visualization

Tool	Description	Lang	Paper
UMAP (umap-learn)	Manifold-learning dimensionality reduction (fuzzy topological graph); widely used for 2-D visualization of single-cell data.	Python	arXiv 2018 (preprint)
openTSNE	Fast, extensible t-SNE (FFT interpolation, Barnes-Hut) that can add new points to existing embeddings.	Python	Journal of Statistical Software 2024
leidenalg	Implementation of Leiden community detection, which guarantees well-connected communities; clustering backend for Scanpy's sc.tl.leiden.	Python	Scientific Reports 2019
PHATE	Diffusion-based potential-distance embedding that preserves local and global structure, highlighting continuous transitions and branches.	Python	Nature Biotechnology 2019
clustree	Plots clusterings at several resolutions as a tree, showing how cells move between clusters to guide resolution choice.	R	GigaScience 2018

Cell type annotation

Tool	Description	Lang	Paper
CellTypist	Automated annotation with logistic-regression classifiers and a library of curated pre-trained immune and tissue models.	Python	Science 2022
ScType	Fast, fully automated marker-based annotation scoring positive and negative markers from the ScType database.	R	Nature Communications 2022
CellAssign	Probabilistic model assigning cells to predefined types from known marker genes, without a reference dataset.	R	Nature Methods 2019
SingleR	Reference-based annotation correlating each cell with labelled reference profiles, refined by iterative fine-tuning.	R	Nature Immunology 2019
Azimuth	Web app and R package mapping query cells onto curated Seurat reference atlases to transfer labels.	R	Cell 2021
CellHint	Harmonises cell type labels across independently annotated datasets and uses them to guide integration.	Python	Cell 2023
popV	Ensemble of annotation algorithms with ontology-aware voting, giving consensus labels and per-cell certainty scores.	Python	Nature Genetics 2024

Differential expression & abundance

Tool	Description	Lang	Paper
Milo (miloR)	Differential abundance testing on overlapping kNN-graph neighbourhoods with negative binomial GLMs.	R	Nature Biotechnology 2022
MAST	Hurdle model for single-cell differential expression that adjusts for the cellular detection rate.	R	Genome Biology 2015
muscat	Multi-sample, multi-condition differential state analysis using pseudobulk (edgeR/DESeq2/limma) and mixed models.	R	Nature Communications 2020
scCODA	Bayesian compositional model detecting changes in cell type proportions relative to a reference cell type.	Python	Nature Communications 2021
Libra	One-function interface to many single-cell DE methods, including pseudobulk edgeR/DESeq2/limma and mixed models.	R	Nature Communications 2021
memento	Method-of-moments framework testing differences in mean expression, variability and gene correlation.	Python	Cell 2024
LEMUR	Latent embedding multivariate regression for cluster-free differential expression in multi-condition data.	R	Nature Genetics 2025
propeller (speckle)	Tests cell type proportion differences between groups using transformed proportions and linear models.	R	Bioinformatics 2022

Trajectory, pseudotime & RNA velocity

Tool	Description	Lang	Paper
PAGA	Graph abstraction of cluster connectivity giving topology-preserving maps for trajectory inference. Part of Scanpy.	Python	Genome Biology 2019
scVelo	RNA velocity with a dynamical model of transcriptional kinetics, plus latent time and velocity graphs.	Python	Nature Biotechnology 2020
Dynamo	Reconstructs continuous expression vector fields from RNA velocity (incl. metabolic labeling) for dynamics and in silico perturbation.	Python	Cell 2022
Monocle 3	Learns principal graphs to order cells in pseudotime and find genes varying along trajectories.	R	Nature 2019
CellRank	Markov-chain fate mapping from velocity, pseudotime, real time or other kernels; estimates fate probabilities and drivers.	Python	Nature Methods 2024
Slingshot	Infers lineages over clusters and fits simultaneous principal curves to compute per-lineage pseudotime.	R	BMC Genomics 2018
Palantir	Models differentiation as a Markov chain on diffusion maps to estimate pseudotime and terminal fate probabilities.	Python	Nature Biotechnology 2019
CytoTRACE 2	Interpretable deep learning that predicts each cell's absolute developmental potential (potency) from its expression profile.	R/Python	Nature Methods 2025
RegVelo	Couples RNA velocity with gene regulatory networks to model cell dynamics and predict effects of regulator perturbations.	Python	Cell 2026
dyno (dynverse)	Uniform interface to ~60 trajectory inference methods with method-selection guidelines, from the large TI benchmark.	R	Nature Biotechnology 2019
velocyto	Original RNA velocity: counts spliced/unspliced reads and extrapolates future transcriptional states.	Python	Nature 2018
Waddington-OT (wot)	Optimal transport over time-course scRNA-seq to infer ancestor–descendant couplings and fate trajectories.	Python	Cell 2019
MultiVelo	Extends RNA velocity with chromatin accessibility from single-cell multiome data to model gene regulation dynamics.	Python	Nature Biotechnology 2023
veloVI	Deep generative model of transcriptional dynamics for RNA velocity with uncertainty quantification.	Python	Nature Methods 2024

Gene regulatory networks

Tool	Description	Lang	Paper
SCENIC / pySCENIC	Infers TF regulons from co-expression pruned by cis-regulatory motif enrichment, then scores regulon activity per cell.	Python	Nature Methods 2017
CellOracle	Builds cell-state-specific GRNs using an ATAC-derived base network, then simulates TF perturbations in silico.	Python	Nature 2023
decoupler	Infers TF and pathway activities from prior-knowledge networks (e.g., CollecTRI, PROGENy) using multiple statistical methods.	Python	Bioinformatics Advances 2022
SCENIC+	Infers enhancer-driven GRNs (eRegulons) from paired or unpaired scRNA-seq and scATAC-seq using motif enrichment.	Python	Nature Methods 2023
LINGER	Infers gene regulatory networks from single-cell multiome data, using lifelong learning on large external bulk data.	Python	Nature Biotechnology 2025
Dictys	Infers cell-type-specific and dynamic GRNs along trajectories from scRNA-seq plus scATAC-seq using TF footprinting.	Python	Nature Methods 2023
Arboreto (GRNBoost2)	Scalable Dask-based GRN inference with GRNBoost2 and GENIE3; the co-expression step behind pySCENIC.	Python	Bioinformatics 2019

Cell–cell communication

Ligand–receptor inference from dissociated cells. For spatial methods, see Cell–cell communication & niches.

Tool	Description	Lang	Paper
NicheNet (nichenetr)	Prioritises sender ligands by their predicted regulatory effect on receiver-cell target genes using prior knowledge.	R	Nature Methods 2020
CellChat	Ligand–receptor database with cofactors; models communication probabilities and analyses signaling networks and pathways.	R	Nature Protocols 2025
CellPhoneDB	Curated ligand–receptor database including multi-subunit complexes, with statistical inference of interacting cell type pairs.	Python	Nature Protocols 2025
MultiNicheNet	Differential cell–cell communication for multi-sample, multi-condition designs, combining pseudobulk DE with NicheNet ligand activities.	R	bioRxiv 2023 (preprint)
Scriabin	Single-cell-resolution communication analysis without aggregation, enabling comparisons across samples and conditions.	R	Nature Biotechnology 2024
CellCall	Infers communication by combining ligand–receptor expression with downstream TF activity in receiving cells.	R	Nucleic Acids Research 2021
Tensor-cell2cell	Tensor decomposition of communication scores across samples or conditions to extract context-dependent communication patterns.	Python	Nature Communications 2022

Multi-omics & multimodal integration

Tool	Description	Lang	Paper
Seurat WNN	Weighted nearest neighbour analysis learning per-cell modality weights to jointly analyse RNA with protein or ATAC.	R	Cell 2021
totalVI	Deep generative model jointly modelling CITE-seq RNA and protein, with protein background correction and integration. Part of scvi-tools.	Python	Nature Methods 2021
MultiVI	Deep generative model integrating paired and unpaired scRNA-seq and scATAC-seq (optionally protein) into one latent space. Part of scvi-tools.	Python	Nature Methods 2023
scGLUE	Graph-linked unified embedding integrating unpaired multi-omics via prior regulatory graphs; also infers regulatory links.	Python	Nature Biotechnology 2022
ArchR	Scalable scATAC-seq analysis: QC, clustering, peak calling, motif deviations, scRNA integration and trajectories.	R	Nature Genetics 2021
Signac	Seurat extension for single-cell chromatin data: peaks, motifs, footprinting, peak–gene links and RNA integration.	R	Nature Methods 2021
MOFA+	Bayesian group factor analysis inferring interpretable latent factors shared across modalities and sample groups.	R/Python	Genome Biology 2020
SnapATAC2	Fast Rust-backed package for scATAC-seq and other single-cell omics using matrix-free spectral embedding.	Python	Nature Methods 2024
MaxFuse	Integrates modalities with weakly linked features (e.g., targeted protein vs RNA) via fuzzy-smoothed iterative co-embedding.	Python	Nature Biotechnology 2024

Perturbation analysis & modeling

Tool	Description	Lang	Paper
Mixscape (Seurat)	Classifies CRISPR-targeted cells as perturbed or escaping, then visualises perturbation-specific responses in pooled screens.	R	Nature Genetics 2021
GEARS	Graph neural network on a gene–gene knowledge graph predicting outcomes of unseen single and multi-gene perturbations.	Python	Nature Biotechnology 2024
scGen	VAE with latent vector arithmetic predicting perturbation responses in unseen cell types or species.	Python	Nature Methods 2019
pertpy	scverse framework for perturbation studies: Milo, scCODA, Mixscape, perturbation distances, response spaces and dataset loaders.	Python	Nature Methods 2026
scPerturb	Harmonised resource of single-cell perturbation datasets with energy-statistics tools for comparing perturbation effects.	Python	Nature Methods 2024
CellOT	Neural optimal transport learning maps from control to perturbed single-cell states to predict per-cell responses.	Python	Nature Methods 2023
CPA	Compositional perturbation autoencoder disentangling perturbation, dose and covariates to predict unseen combinations.	Python	Molecular Systems Biology 2023
SCEPTRE	Calibrated, resampling-based association testing between perturbations and gene expression in single-cell CRISPR screens.	R	Genome Biology 2024

Copy number, clonality & immune repertoire

Tool	Description	Lang	Paper
inferCNV	Infers large-scale copy number changes in tumour cells by comparing smoothed expression against reference normal cells.	R
scRepertoire	R toolkit for single-cell TCR/BCR clonotype quantification, diversity and overlap, integrated with Seurat/SingleCellExperiment.	R	PLOS Computational Biology 2025
CopyKAT	Bayesian segmentation of scRNA-seq to infer copy number, separate aneuploid tumour from diploid cells, and find subclones.	R	Nature Biotechnology 2021
scirpy	scverse toolkit for single-cell TCR/BCR data: clonotype definition, expansion, diversity and integration with transcriptomes.	Python	Bioinformatics 2020
Numbat	Haplotype-aware CNV inference combining allele imbalance and expression, reconstructing tumour clonal phylogenies.	R	Nature Biotechnology 2023
Dandelion	Single-cell BCR/TCR V(D)J analysis: reannotation, clonotype networks and V(D)J-informed developmental trajectories.	Python	Nature Biotechnology 2024
SCEVAN	Variational segmentation of scRNA-seq to call copy number, classify malignant cells and resolve clonal substructure.	R	Nature Communications 2023

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🤖 AI & Foundation Models

Single-cell foundation models

Large models pretrained on millions of cells.

Tool	Description	Lang	Paper
scGPT	Generative pretrained transformer trained on 33M+ human cells; fine-tuned for annotation, batch integration, perturbation prediction and GRN inference.	Python	Nature Methods 2024
State	Arc Institute virtual-cell model predicting perturbation responses over cell sets; trained on ~170M observational and 100M+ perturbed cells.	Python	Cell 2026
scFoundation	100M-parameter asymmetric transformer pretrained on 50M+ human cells covering ~20k genes, using read-depth-aware masked pretraining.	Python	Nature Methods 2024
scBERT	BERT-style transformer pretrained on ~1.1M unlabeled PanglaoDB cells, then fine-tuned for cell type annotation.	Python	Nature Machine Intelligence 2022
UCE (Universal Cell Embeddings)	Zero-shot, species-agnostic cell embeddings using protein-language-model gene tokens; built a 36M-cell atlas spanning eight species.	Python	Nature 2026
SCimilarity	Metric-learning model for fast cell-similarity search; queries a 23.4M-cell atlas from 412 human scRNA-seq studies.	Python	Nature 2025
TranscriptFormer	Generative cross-species model (CZI) trained on up to 112M cells from 12 species spanning 1.53 billion years of evolution.	Python	Science 2026
scPRINT	Transformer pretrained on 50M+ CELLxGENE cells, designed for gene network inference plus denoising, batch correction and label prediction.	Python	Nature Communications 2025
GeneCompass	Cross-species model pretrained on ~100M human and mouse cells, integrating prior knowledge such as GRNs and promoter sequences.	Python	Cell Research 2024
CellFM	800M-parameter RetNet-style model pretrained on ~100M human cells using MindSpore; annotation, perturbation and gene-function tasks.	Python	Nature Communications 2025
CellPLM	Cell language model treating cells as tokens and tissues as sentences; pretraining includes spatial data to learn cell-cell relations.	Python	ICLR 2024
scMulan	368M-parameter generative language model pretrained on 10M cells with metadata; zero-shot annotation, integration and conditional generation.	Python	RECOMB (LNCS) 2024
scLong	Billion-parameter model pretrained on 48M cells, attending over all ~28k human genes to capture long-range gene context.	Python	Nature Communications 2026
Geneformer	Transformer using rank-value gene encoding; V1 pretrained on ~30M human cells, V2 on ~104M; supports in silico perturbation.	Python	Nature 2023

Spatial & multimodal foundation models

Models that learn from spatial context, histology or several modalities.

Tool	Description	Lang	Paper
Nicheformer	Transformer pretrained on SpatialCorpus-110M (dissociated and spatial human/mouse cells); transfers spatial context to scRNA-seq data.	Python	Nature Methods 2025
Novae	Self-supervised graph attention model trained on ~30M spatial cells across 18 tissues; zero-shot spatial domains and batch correction.	Python	Nature Methods 2025
Loki (OmiCLIP)	Contrastive H&E-transcriptomics model trained on 2.2M Visium image-expression pairs; supports alignment, annotation, deconvolution and expression prediction.	Python	Nature Methods 2025
scGPT-spatial	scGPT continually pretrained on SpatialHuman30M (Visium, Visium HD, MERFISH, Xenium) with mixture-of-experts decoders for spatial tasks.	Python	bioRxiv 2025 (preprint)
SToFM	Multi-scale spatial transcriptomics model using an SE(2) Transformer; pretrained on SToCorpus-88M (88M cells, six technologies).	Python	ICML 2025
STPath	Generative model predicting spatial expression of 38,984 genes from whole-slide H&E images; trained on HEST-1k and STimage-1K4M.	Python	npj Digital Medicine 2025
CELLama	Turns cell expression and metadata into sentences embedded by a language model; cell typing and spatial-context analysis.	Python	Advanced Science 2026
SpatialFormer	CNN-transformer pretrained on 17M Xenium cells, learning subcellular transcript layout and niche context; annotation, batch correction, co-localization.	Python	Nature Computational Science 2026

LLMs & agents

Language models and agents that annotate cells or run analyses.

Tool	Description	Lang	Paper
Biomni	General-purpose biomedical agent combining LLM reasoning, retrieval and code execution over curated tools, databases and protocols.	Python	Science 2026
Cell2Sentence (C2S-Scale)	Encodes cells as ranked gene-name sentences for LLM training; C2S-Scale extends this to Gemma-2 models up to 27B parameters.	Python	ICML 2024
GenePT	Gene and cell embeddings built from GPT-3.5 text embeddings of gene descriptions, without expression-based pretraining.	Python	Nature Biomedical Engineering 2025
CellVoyager	LLM agent that autonomously proposes and runs new scRNA-seq analyses in Jupyter notebooks, re-analyzing published datasets.	Python	Nature Methods 2026
GPTCelltype	R package and study showing GPT-4 annotates cell types from marker genes, agreeing well with manual annotations.	R	Nature Methods 2024
CellWhisperer	Contrastive transcriptome-text embedding trained on ~1M RNA-seq profiles plus an LLM for chat-based exploration in CELLxGENE.	Python	Nature Biotechnology 2025
SpatialAgent	LLM agent for spatial biology: gene-panel design, cell annotation, cell-cell communication analysis and hypothesis generation.	Python	bioRxiv 2025 (preprint)
CASSIA	Multi-agent LLM framework for reference-free, interpretable cell type annotation with validation and quality scoring.	Python	Nature Communications 2026

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📊 Benchmarks & Evaluation

Benchmarks & evaluation

Independent comparisons to consult before picking a method.

Tool	Description	Lang	Paper
Open Problems in Single-Cell Analysis	Living, community-guided benchmarking platform with formalized single-cell tasks, datasets, metrics and public leaderboards.	Python/R	Nature Biotechnology 2025
scIB	Benchmark of 68 method-preprocessing combinations on 13 atlas-level integration tasks with 14 metrics; reusable scib metrics package.	Python	Nature Methods 2022
dynbenchmark	Comparison of 45 trajectory inference methods on 110 real and 229 synthetic datasets; underlies the dynverse toolkit.	R	Nature Biotechnology 2019
BEELINE	Framework benchmarking GRN inference from scRNA-seq using synthetic networks, curated Boolean models and experimental datasets.	Python	Nature Methods 2020
Virtual Cell Challenge	Arc Institute's annual competition predicting CRISPRi perturbation responses; 2026 edition tests zero-shot transfer to unseen cell lines.	Python	Cell 2025
SpatialBenchmarking (Li et al.)	Benchmark of 16 methods integrating scRNA-seq with spatial data for gene imputation and spot deconvolution (45 paired datasets).	Python	Nature Methods 2022
scPerturBench	Benchmark of 27 genetic and chemical perturbation-response methods on 29 datasets, testing generalization to unseen contexts and perturbations.	Python	Nature Methods 2026
Linear baselines for perturbation prediction	Shows foundation and deep-learning perturbation models do not beat simple linear/additive baselines on single and double perturbations.	R	Nature Methods 2025
Zero-shot evaluation of single-cell foundation models	Shows zero-shot scGPT and Geneformer embeddings can underperform HVG selection and scVI for cell clustering and batch integration.	Python	Genome Biology 2025
Systema	Evaluation framework separating perturbation-specific effects from systematic control-vs-perturbed variation that inflates standard metrics.	Python	Nature Biotechnology 2026
SDMBench (spatial clustering benchmark)	Benchmark of 13 spatial clustering/domain methods on 34 spatial transcriptomics datasets; accuracy, continuity, marker detection, scalability.	Python	Nature Methods 2024
PertEval-scFM	Standardized framework testing whether zero-shot scFM embeddings improve perturbation-effect prediction; finds limited gains over simple baselines.	Python	ICML 2025
Spotless	Reproducible Nextflow benchmark of spatial deconvolution methods on simulated and real datasets.	R	eLife 2024
BenchmarkST	Benchmark of clustering, slice alignment and integration methods for spatial transcriptomics across many datasets.	Python	Genome Biology 2024

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📦 Data

Atlases, data portals & databases

Resource	Description	Paper
HEST-1k	1,000+ spatial transcriptomics samples paired with H&E whole-slide images, plus loading library and expression-prediction benchmark.	NeurIPS 2024
Tabula Muris / Tabula Muris Senis	Single-cell transcriptomic atlases of 20 mouse organs (Tabula Muris) and of tissue ageing (Tabula Muris Senis).	Nature 2018
CZ CELLxGENE Discover & Census	Curated, standardized single-cell data platform with web exploration and the Census API for programmatic Python/R access.	Nucleic Acids Research 2025
Allen Brain Cell Atlas (ABC Atlas)	Allen Institute platform to explore and download brain cell-type atlases: whole mouse brain scRNA-seq/MERFISH, human brain and more.	Nature 2023
spatialLIBD	R/Bioconductor package and web apps to access and explore LIBD human brain Visium datasets, such as DLPFC.	BMC Genomics 2022
Broad Single Cell Portal	Self-service Broad portal for sharing, visualizing and downloading single-cell and spatial studies with interactive gene views.	bioRxiv 2023 (preprint)
Tabula Sapiens	Multi-organ human single-cell transcriptomic reference atlas; Tabula Sapiens 2.0 spans ~1.1 million cells from 28 tissues.	Science 2022
UCSC Cell Browser	Web viewer hosting hundreds of published single-cell datasets, plus open-source tools to build your own browser.	Bioinformatics 2021
Human Cell Atlas Data Portal	Official repository for Human Cell Atlas data: browse and download raw sequencing data, metadata and expression matrices.	eLife 2017
DISCO	Database of deeply integrated human single-cell omics data, with harmonized metadata, tissue atlases, and online annotation and integration tools.	Nucleic Acids Research 2022
Single Cell Expression Atlas (EMBL-EBI)	EMBL-EBI resource reanalysing public single-cell RNA-seq datasets with standardized pipelines across many species, including marker genes.	Nucleic Acids Research 2024
CellMarker 2.0	Manually curated database of human and mouse cell-type markers, with web tools for single-cell data analysis.	Nucleic Acids Research 2023
PanglaoDB	Database of uniformly processed mouse and human scRNA-seq samples and curated cell-type marker genes.	Database (Oxford) 2019
SODB (Spatial Omics DataBase)	Spatial omics database with >2,400 experiments from >25 technologies, unified downloads and interactive analysis modules.	Nature Methods 2023
STOmicsDB	CNGB spatial transcriptomics hub for data archiving and sharing, with curated, annotated public datasets and visualization.	Nucleic Acids Research 2024
HuBMAP Data Portal	NIH Human BioMolecular Atlas Program portal for single-cell, spatial and imaging maps of healthy human tissues.	Nature 2019
HTAN Data Portal	NCI Human Tumor Atlas Network portal with single-cell, spatial and imaging data charting cancer transitions.	Cell 2020
10x Genomics Datasets	Free example datasets from 10x Chromium, Visium (including HD) and Xenium platforms, with processed outputs.

Simulation

Synthetic data with known ground truth for benchmarking.

Tool	Description	Lang	Paper
Splatter	Bioconductor package simulating scRNA-seq counts with groups, paths and batches; offers a common interface to other simulators.	R	Genome Biology 2017
scDesign3	Fits interpretable statistical models to real data to generate realistic synthetic single-cell and spatial omics data.	R	Nature Biotechnology 2024
SERGIO	Python simulator generating single-cell expression from user-defined gene regulatory networks, at steady state or along differentiation.	Python	Cell Systems 2020
dyngen	Multi-modal simulator of single cells undergoing dynamic processes, driven by gene regulatory networks, for benchmarking methods.	R	Nature Communications 2021
scMultiSim	Simulates single-cell multi-omics and spatial data guided by gene regulatory networks and cell–cell interactions.	R	Nature Methods 2025
scCube	Python package for reproducible, platform-diverse simulation of spatial transcriptomics with customizable cell-type spatial patterns.	Python	Nature Communications 2024
SymSim	R package simulating scRNA-seq with extrinsic, intrinsic (kinetic) and technical variation, plus tree-based population structure.	R	Nature Communications 2019
SRTsim	R framework for reproducible spatially resolved transcriptomics simulation that preserves spatial expression patterns, for benchmarking.	R	Genome Biology 2023

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awesome-single-cell – The largest community list of single-cell software and data resources.
awesome_spatial_omics – Tools and notes for spatial omics.
awesome-spatial-omics – Spatial omics technologies and methods.
awesome-single-cell-foundation – Papers on single-cell foundation models.

Contributing

Contributions are welcome! Please read the contributing guide first. If you spot a dead link, an archived repository or a wrong paper, please open an issue.

Star History

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wrab12/awesome-spatial-transcriptomics

A curated list of tools, foundation models, datasets and tutorials for spatial transcriptomics and single-cell analysis, ordered the way an analysis goes.

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updated Oct 12, 2026

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	I made a list of spatial transcriptomics tools ordered by analysis step (340 entries, every link and DOI checked). What's missing? (r/bioinformatics) When I got into spatial transcriptomics, it was hard to tell which tool fits which step, so I put together the list I wish I'd had: [https://github.com/wrab12/awesome-spatial-transcriptomics](https://github.com/wrab12/awesome-spatial-transcriptomics) There are already good lists…	8	Oct 8, 2026

README

Awesome Spatial Transcriptomics

A curated list of tools, foundation models, datasets, tutorials and papers for spatial transcriptomics and the single-cell methods it builds on, ordered the way an analysis actually goes.

Ordered like an analysis. Sections run from technologies and preprocessing to domains, deconvolution, alignment, cell–cell communication and spatiotemporal modeling.
Spatial and single-cell together. Spatial analysis relies on single-cell tools for annotation, integration and trajectories, so both are covered.
Up to date. Includes work from 2023–2026: tools for subcellular platforms such as Visium HD and Xenium, foundation models, LLM agents and recent benchmarks.
Checked. Every repository and paper link was verified when added, and the star badges update automatically.
A place to start. If you are new to the field, begin with the free books, courses and reviews in Start Here.

Within each table, tools are sorted by GitHub stars. Stars measure popularity, not quality, so check the benchmarks before picking a method.

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Spatial Technologies
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🧭 Start Here

Best-practice guides & books

Free books that walk through a complete analysis.

Single-cell Best Practices – Open Jupyter Book on scverse-based analysis of single-cell and spatial omics, from preprocessing to multimodal integration. Nature Reviews Genetics 2023
Orchestrating Single-Cell Analysis with Bioconductor (OSCA) – Bioconductor online book covering scRNA-seq analysis in R, from data import and QC to multi-sample workflows. Nature Methods 2020
Orchestrating Spatial Transcriptomics Analysis with Bioconductor (OSTA) – Bioconductor online book with tested R workflows for sequencing- and imaging-based spatial transcriptomics data. bioRxiv 2025 (preprint)
A Practical Guide to Spatial Transcriptomics: Lessons from over 1000 Samples – Practical guide for Visium, Visium HD and Xenium projects: experimental design, tissue handling, sequencing and analysis. Trends in Biotechnology 2026

Courses & hands-on tutorials

Notebooks and vignettes you can run end to end.

scverse tutorials (Scanpy and ecosystem) – Curated hub of maintained Python tutorials for Scanpy, AnnData, muon, scvi-tools, Squidpy, SpatialData and other scverse packages. Nature Biotechnology 2023
scvi-tools tutorials – Notebooks for scvi-tools deep generative models: integration, reference mapping, multimodal analysis and spatial deconvolution. Nature Biotechnology 2022
Squidpy tutorials – Spatial analysis tutorials (graphs, neighborhood enrichment, spatial statistics, image features) for Visium, Xenium, MERFISH, Slide-seq and more. Nature Methods 2022
SpatialData tutorials – Notebooks for loading, aligning, querying and visualizing multi-technology spatial omics data with the SpatialData framework. Nature Methods 2025
Seurat vignettes (incl. spatial) – Official R vignettes from guided PBMC clustering to integration, multimodal analysis and sequencing- and imaging-based spatial data. Nature Biotechnology 2024
HBC Introduction to single-cell RNA-seq – Harvard Chan Bioinformatics Core workshop: design, QC, normalization, integration, clustering and marker genes with Seurat or Scanpy.
HBC Introduction to Spatial Transcriptomics – Harvard Chan workshop on Visium HD in Seurat: QC, clustering, RCTD deconvolution, BANKSY domains, Moran's I, CellChat.
Analysis of single cell RNA-seq data (Sanger / Hemberg lab course) – Classic Cambridge/Sanger course book: scRNA-seq technologies, raw data processing, QC, normalization, clustering and integration in R.
Galaxy Training Network: Single Cell – Galaxy Training Network tutorials and learning pathways for single-cell analysis, GUI or notebook based, including spatial transcriptomics. GigaScience 2020
Voyager tutorials – Vignettes applying geospatial statistics (Moran's I, local indicators, Lee's L) to spatial omics via SpatialFeatureExperiment. bioRxiv 2023 (preprint)
Giotto Suite tutorials – Technology-agnostic spatial omics tutorials in R: Visium/HD, Xenium, CosMx, MERFISH, CODEX; domains, deconvolution, multi-sample integration. Nature Methods 2025
10x Genomics Analysis Guides – Vendor tutorials and method overviews for Chromium, Visium/Visium HD and Xenium data, with Colab-ready notebooks.
NBIS single-cell RNA-seq workshop – Regularly updated NBIS course with parallel Seurat, Bioconductor and Scanpy labs from QC to cell typing and trajectories.
SIB Single Cell Transcriptomics course – SIB three-day course material in R (Seurat, Bioconductor): QC, integration, clustering, annotation, DE, enrichment and trajectories.

Key reviews

Reviews worth reading before choosing methods.

Spatial architecture of development and disease (Lázár & Lundeberg) – Recent review of how spatial omics reveals tissue organization in development and disease. Nature Reviews Genetics 2026
Towards multimodal foundation models in molecular cell biology (Cui et al.) – Perspective on foundation models pretrained across genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial profiling. Nature 2025
Transformers in single-cell omics: a review and new perspectives (Szałata et al.) – Explains transformer architectures and reviews their single-cell applications, including foundation models, with limitations and future directions. Nature Methods 2024
How to build the virtual cell with artificial intelligence: Priorities and opportunities (Bunne et al.) – Perspective on AI virtual cells: multiscale, multimodal neural network models that represent and simulate molecules, cells and tissues. Cell 2024
Unlocking the power of spatial omics with AI (Coleman, Schroeder & Li) – Short Comment on how AI methods can help analyze and integrate complex spatial omics datasets. Nature Methods 2024
Best practices for single-cell analysis across modalities (Heumos et al.) – Benchmark-based best-practice workflows for single-cell RNA, chromatin, surface protein, immune repertoire and spatial data. Nature Reviews Genetics 2023
Methods and applications for single-cell and spatial multi-omics (Vandereyken et al.) – Reviews single-cell and spatial multi-omics technologies, the computational integration strategies they need, and their applications. Nature Reviews Genetics 2023
The expanding vistas of spatial transcriptomics (Tian, Chen & Macosko) – Reviews how spatial transcriptomics technologies evolved in sensitivity, multiplexing and throughput, and what they enable. Nature Biotechnology 2023
The dawn of spatial omics (Bressan, Battistoni & Hannon) – Systematic catalog of spatial omics technology families, their principles and limitations, and the field's main challenges. Science 2023
Museum of spatial transcriptomics (Moses & Pachter) – Curated history of spatial transcriptomics since 1987, with trend analysis of technologies, tissues and computational methods. Nature Methods 2022
Spatial components of molecular tissue biology (Palla et al.) – Groups spatial transcriptomics and proteomics analysis problems and algorithms by tissue length scale, outlining open computational challenges. Nature Biotechnology 2022
Computational principles and challenges in single-cell data integration (Argelaguet et al.) – Defines horizontal, vertical and diagonal integration of single-cell data and reviews methods, assumptions and open challenges. Nature Biotechnology 2021
Deciphering cell–cell interactions and communication from gene expression (Armingol et al.) – Reviews how cell–cell communication is inferred from transcriptomic data, mainly ligand–receptor approaches, and the tools used. Nature Reviews Genetics 2021
Method of the Year: spatially resolved transcriptomics (Marx) – Nature Methods feature naming spatially resolved transcriptomics Method of the Year 2020, surveying its technologies and prospects. Nature Methods 2021
Exploring tissue architecture using spatial transcriptomics (Rao et al.) – Reviews sequencing- and imaging-based spatial transcriptomics technologies and the range of analyses applied to their data. Nature 2021
Eleven grand challenges in single-cell data science (Lähnemann et al.) – Community overview of major open computational challenges in single-cell data science and the research needed to address them. Genome Biology 2020
Current best practices in single-cell RNA-seq analysis: a tutorial (Luecken & Theis) – Step-by-step tutorial and recommendations for standard scRNA-seq analysis, from QC and normalization to clustering and trajectories. Molecular Systems Biology 2019

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🔬 Spatial Technologies

Spatial technologies

Landmark platforms and their method papers, grouped by how they measure and sorted by year.

Sequencing-based (spatially barcoded capture, then sequencing)

Technology	Description	Paper
Spatial Transcriptomics (ST)	Barcoded oligo-dT spot arrays capture mRNA from tissue sections for genome-wide spatial profiling; foundational array method (100 µm spots).	Science 2016
Slide-seq / Slide-seqV2	Tissue placed on a monolayer of DNA-barcoded 10 µm beads whose positions are decoded by in situ sequencing.	Science 2019
HDST	High-definition spatial transcriptomics: RNA captured on a dense, spatially barcoded bead array at 2 µm resolution.	Nature Methods 2019
DBiT-seq	Microfluidic deterministic barcoding: crossed channel sets create a 2D pixel grid for co-profiling mRNA and proteins in tissue.	Cell 2020
Seq-Scope	Repurposes Illumina flow-cell clusters as barcoded capture arrays; pixels ~0.5–0.8 µm apart for submicrometer spatial transcriptomics.	Cell 2021
Stereo-seq	DNA nanoball-patterned arrays give nanoscale capture spots over centimeter-scale areas; debuted with a mouse organogenesis atlas (MOSTA).	Cell 2022
Slide-tags	Spatial barcodes from a bead array tag nuclei in intact tissue, enabling spatially resolved single-nucleus RNA, ATAC and multimodal profiling.	Nature 2024
Open-ST	Open-source, low-cost sequencing-based method on patterned Illumina flow cells with subcellular resolution and 3D virtual tissue reconstruction.	Cell 2024
Visium / Visium HD (10x Genomics)	10x Genomics capture arrays: Visium (55 µm spots) and Visium HD (gapless 2 µm barcoded squares, usually binned).	Nature Genetics 2025

Imaging-based (in situ hybridization or sequencing, read by microscopy)

Technology	Description	Paper
MERFISH	Multiplexed error-robust FISH: combinatorial binary barcodes read over sequential imaging rounds profile hundreds to thousands of RNAs.	Science 2015
STARmap / STARmap PLUS	In situ sequencing of hydrogel-embedded intact tissue in 3D; STARmap PLUS adds protein co-detection at subcellular resolution.	Science 2018
osmFISH	Cyclic, non-barcoded single-molecule FISH (ouroboros smFISH) mapping cell-type markers across mouse somatosensory cortex.	Nature Methods 2018
seqFISH+	Sequential FISH with 60 pseudocolors images ~10,000 genes at super-resolution in single cells within tissue.	Nature 2019
CosMx SMI	Spatial molecular imaging: cyclic hybridization of fluorescent barcodes measured 980 RNAs and 108 proteins in FFPE tissue.	Nature Biotechnology 2022
Xenium (10x Genomics)	10x in situ platform: padlock probes, rolling-circle amplification and cyclic imaging detect targeted gene panels at subcellular resolution.	Nature Communications 2023
EEL FISH	Electrophoretically transfers RNA from tissue onto a capture surface, then decodes it by multiplexed smFISH for fast imaging.	Nature Biotechnology 2023

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📍 Spatial Transcriptomics Analysis

Spatial frameworks

General-purpose toolkits and data structures for spatial omics.

Tool	Description	Lang	Paper
Seurat (spatial vignettes)	Seurat workflows for sequencing- and imaging-based spatial data (Visium, Visium HD, Slide-seq, Xenium, CosMx, MERFISH).	R	Nature Biotechnology 2024
Squidpy	scverse toolkit for spatial omics: spatial graphs, neighborhood enrichment, co-occurrence, ligand–receptor analysis and image features.	Python	Nature Methods 2022
SpatialData	Universal data framework (Zarr/OME-NGFF) unifying images, labels, points, shapes and tables across spatial omics technologies.	Python	Nature Methods 2025
Giotto Suite	Modular R ecosystem for technology-agnostic, multiscale spatial multi-omics analysis, integration and visualization.	R	Nature Methods 2025
stLearn	Integrates histology images, spatial coordinates and expression for normalization, clustering, spatial trajectories and cell–cell interactions.	Python	Nature Communications 2023
SPATA2	R framework for spatial transcriptomics emphasizing histology-guided analyses such as spatial gradient screening along tissue axes.	R	Nature Communications 2024
Voyager / SpatialFeatureExperiment	Brings geospatial exploratory statistics (e.g., Moran's I, local indicators) to spatial omics on SpatialFeatureExperiment geometries.	R	bioRxiv 2023 (preprint)
semla	Seurat-compatible R toolkit for Visium/ST analysis, visualization, image alignment and spatial utilities; successor of STUtility.	R	Bioinformatics 2023
SpatialExperiment	Bioconductor S4 class extending SingleCellExperiment with spatial coordinates and images; core data structure for R spatial tools.	R	Bioinformatics 2022

Cell segmentation & preprocessing

From images and transcripts or bins to cells.

Tool	Description	Lang	Paper
Cellpose	Generalist deep-learning cell and nucleus segmentation predicting spatial flow fields; supports human-in-the-loop training and 3D.	Python	Nature Methods 2021
StarDist	Deep-learning object detection with star-convex polygons; accurate nucleus segmentation in crowded 2D and 3D images.	Python	MICCAI 2018 (LNCS)
Mesmer (DeepCell)	Deep-learning whole-cell and nuclear segmentation for multiplexed tissue images, trained on the TissueNet dataset.	Python	Nature Biotechnology 2022
Sopa	Technology-invariant, scalable SpatialData-based pipeline for segmentation, aggregation and annotation across imaging-based spatial omics and Visium HD.	Python	Nature Communications 2024
Baysor	Bayesian segmentation of imaging-based ST from molecule positions and gene composition, optionally guided by a prior segmentation.	C++	Nature Biotechnology 2022
Proseg	Probabilistic segmentation that simulates cell shapes (cellular Potts model) to best explain transcript positions; fast, unsupervised.	Rust	Nature Methods 2025
bin2cell	Reconstructs cells from Visium HD 2 µm bins using StarDist nuclei from H&E and expression images plus label expansion.	Python	Bioinformatics 2024
ENACT	End-to-end Visium HD pipeline: cell segmentation, bin-to-cell assignment and cell-type annotation across whole tissue sections.	Python	Bioinformatics 2025
Segger	Graph neural network that assigns transcripts to cells via link prediction on a heterogeneous transcript–cell graph.	Python	bioRxiv 2025 (preprint)
Space Ranger	Official 10x pipelines for Visium/Visium HD: alignment, image registration, tissue detection, binning; v4+ adds nucleus-based cell segmentation.	Rust

Spatially variable genes

Genes whose expression follows tissue structure.

Tool	Description	Lang	Paper
SpatialDE	Gaussian-process regression tests each gene for spatial variance; automatic expression histology groups genes into spatial patterns.	Python	Nature Methods 2018
Hotspot	Local autocorrelation on a cell–cell neighbor graph (spatial or transcriptional) to find informative genes and gene modules.	Python	Cell Systems 2021
MERINGUE	Spatial auto- and cross-correlation on Voronoi-based neighbor graphs; robust to non-uniform cell densities.	R	Genome Research 2021
SPARK / SPARK-X	SPARK: spatial generalized linear mixed model on raw counts; SPARK-X: fast non-parametric covariance test for large datasets.	R	Nature Methods 2020
nnSVG	Scalable SVG detection using nearest-neighbor Gaussian processes with gene-specific length scales; linear in number of spots.	R	Nature Communications 2023
Celina	Spatially varying coefficient model detecting cell type-specific spatially variable genes in spot- or single-cell-resolution data.	R	Nature Communications 2025
sepal	Simulates diffusion of each gene's expression; genes slow to reach homogeneity are ranked as spatially structured.	Python	Bioinformatics 2021
SpaGFT	Graph Fourier transform of expression on spatial graphs identifies SVGs and tissue modules; enhances downstream ML tasks.	Python	Nature Communications 2024

Spatial domains & clustering

Tissue regions from expression plus spatial context.

Tool	Description	Lang	Paper
SpaGCN	Graph convolutional network combining expression, location and histology to find spatial domains and domain-specific SVGs.	Python	Nature Methods 2021
CellCharter	Aggregates features from multi-hop spatial neighbors and clusters with Gaussian mixtures to find niches across samples.	Python	Nature Genetics 2024
BayesSpace	Bayesian clustering with a Markov random field prior for spatial domains; enhances Visium/ST to sub-spot resolution.	R	Nature Biotechnology 2021
BANKSY	Augments each cell's expression with neighborhood mean and gradient features, unifying cell typing and domain segmentation.	R	Nature Genetics 2024
GraphST	Graph self-supervised contrastive learning for spatial clustering, multi-section integration and scRNA-seq-to-spatial cell-type deconvolution.	Python	Nature Communications 2023
DeepST	Combines histology morphology features, expression and location with graph and denoising autoencoders to identify spatial domains.	Python	Nucleic Acids Research 2022
SEDR	Masked graph autoencoder plus deep autoencoder learns spatial embeddings for clustering, denoising and batch integration.	Python	Genome Medicine 2024
STAGATE	Graph attention autoencoder learning spatially aware embeddings for domain identification and denoising, including 3D tissue.	Python	Nature Communications 2022
spaVAE	Gaussian-process VAE capturing spatial correlation for clustering, denoising, imputation and resolution enhancement; ATAC/multi-omics variants.	Python	Nature Methods 2024
BASS	Bayesian hierarchical model jointly performing cell-type clustering and spatial domain detection across multiple tissue sections.	R	Genome Biology 2022
SpaceFlow	Spatially regularized deep graph network learning embeddings for domains and pseudo-spatiotemporal maps of tissues.	Python	Nature Communications 2022

Deconvolution & single-cell mapping

Cell-type composition of spots and mapping of single cells onto tissue.

Tool	Description	Lang	Paper
DestVI (scvi-tools)	Conditional deep generative model inferring cell-type proportions and continuous within-type state variation per spot.	Python	Nature Biotechnology 2022
RCTD (spacexr)	Supervised Poisson model with platform-effect normalization decomposing spots into cell types; spacexr also includes C-SIDE DE testing.	R	Nature Biotechnology 2022
cell2location	Hierarchical Bayesian model mapping fine-grained cell types from scRNA-seq references to spatial data as absolute abundances.	Python	Nature Biotechnology 2022
Tangram	Deep-learning alignment of scRNA-seq profiles onto spatial data to map cells, project genes and deconvolve spots.	Python	Nature Methods 2021
SPOTlight	Seeded NMF regression using cell-type marker genes from scRNA-seq to deconvolve spatial spots.	R	Nucleic Acids Research 2021
STdeconvolve	Reference-free deconvolution using latent Dirichlet allocation topic modeling of multicellular spatial pixels.	R	Nature Communications 2022
CytoSPACE	Assigns individual scRNA-seq cells to spots by convex optimization, respecting estimated cell numbers per spot.	Python	Nature Biotechnology 2023
CARD	Deconvolution with a conditional autoregressive prior on spatial composition; builds refined-resolution maps; reference-free mode available.	R	Nature Biotechnology 2022
CellTrek	Maps single cells to tissue coordinates via scRNA-seq–spatial co-embedding and random-forest similarity learning.	R	Nature Biotechnology 2022
stereoscope	Negative-binomial probabilistic model inferring per-spot cell-type proportions from a single-cell reference.	Python	Communications Biology 2020
Redeconve	Regularized non-negative regression using single cells as reference, deconvolving spots into thousands of fine cell states.	R	Nature Communications 2023

Alignment, integration & 3D reconstruction

Registering slices, integrating samples and building 3D tissue.

Tool	Description	Lang	Paper
Spateo	3D spatiotemporal framework: slice alignment, whole-embryo 3D reconstruction, morphometric vector fields, spatial domains and cell–cell interactions.	Python	Cell 2024
STalign	Diffeomorphic metric mapping (LDDMM) aligns single-cell-resolution ST slices to each other or to 3D reference atlases.	Python	Nature Communications 2023
PASTE	Fused Gromov–Wasserstein optimal transport for pairwise alignment of adjacent ST slices and integration into a consensus center slice.	Python	Nature Methods 2022
SLAT	Graph neural network with adversarial matching aligns heterogeneous single-cell spatial slices across technologies and modalities.	Python	Nature Communications 2023
STitch3D	Jointly models multiple 2D slices with an scRNA-seq reference to reconstruct 3D tissue regions and cell-type distributions.	Python	Nature Machine Intelligence 2023
SPACEL	Deep-learning toolkit: Spoint deconvolution, Splane multi-slice domains, and Scube alignment and stacking of consecutive slices into 3D.	Python	Nature Communications 2023
STAligner	Graph attention autoencoder with spot-triplet loss integrates slices across conditions, technologies and developmental stages; supports 3D alignment.	Python	Nature Computational Science 2023
PASTE2	Partial fused Gromov–Wasserstein OT aligns partially overlapping slices, optionally using histology, enabling 3D stacking.	Python	Genome Research 2023
CAST	Self-supervised graph embeddings plus rigid and free-form alignment to search and match spatial samples at single-cell resolution.	Python	Nature Methods 2024
GPSA	Deep Gaussian process model that maps multiple spatial genomics and histology slices into a common coordinate system.	Python	Nature Methods 2023
SpatialZ	Generates virtual single-cell slices between measured sections to build dense 3D cell atlases from planar ST data.	Python	Nature Methods 2026
SANTO	Coarse-to-fine alignment and stitching of partially overlapping spatial omics slices, in 2D or 3D and across omics types.	Python	Nature Communications 2024

Cell–cell communication & niches

Spatially aware signaling, interaction and niche analysis.

Tool	Description	Lang	Paper
LIANA+	All-in-one cell–cell communication framework unifying many ligand–receptor methods, with spatially informed bivariate metrics and multi-view (MISTy) modeling.	Python	Nature Cell Biology 2024
COMMOT	Collective optimal transport infers ligand–receptor signaling and its spatial direction, accounting for competition among ligands and receptors.	Python	Nature Methods 2023
NicheCompass	Interpretable graph deep learning using prior interaction-pathway knowledge to learn signaling-aware embeddings and characterize cell niches at scale.	Python	Nature Genetics 2025
NCEM	Node-centric expression models (linear to graph neural networks) predict a cell's expression from its spatial neighbors to infer communication.	Python	Nature Biotechnology 2023
FlowSig	Graphical causal modeling of intercellular flows linking incoming signals, intracellular gene modules and outgoing signals.	Python	Nature Methods 2024
SpaTalk	Knowledge-graph-based inference of ligand–receptor–target signaling between spatially proximal cells; deconvolves spot data into single cells.	R	Nature Communications 2022
MISTy (mistyR)	Explainable multiview machine learning that dissects intracellular and neighborhood (juxta-/para-view) relationships among markers in spatial omics.	R	Genome Biology 2022
CellNEST	Graph attention model that detects cell–cell communication and multi-hop relay networks from spatial transcriptomics.	Python	Nature Methods 2025
SpaOTsc	Structured optimal transport maps scRNA-seq cells to spatial locations and infers spatially constrained cell–cell signaling.	Python	Nature Communications 2020
SpatialDM	Bivariate Moran's statistic with an analytical null detects spatially co-expressed ligand–receptor pairs and local interaction hotspots, at scale.	Python	Nature Communications 2023

Super-resolution, imputation & histology-to-expression

Higher resolution, more genes, or expression predicted from H&E.

Tool	Description	Lang	Paper
gimVI (scvi-tools)	Joint generative (VAE) model of scRNA-seq and spatial data that imputes genes missing from targeted spatial panels.	Python	arXiv 2019 (preprint)
iStar	Combines hierarchical histology image features with spot-level ST to predict near-single-cell super-resolution expression and annotate tissue.	Python	Nature Biotechnology 2024
ST-Net	Early CNN model predicting spatially resolved expression of hundreds of genes from breast cancer H&E image patches.	Python	Nature Biomedical Engineering 2020
BLEEP	Bi-modal contrastive learning aligns H&E patch and expression embeddings, then predicts expression by retrieving similar reference spots.	Python	NeurIPS 2023
SpatialScope	Deep generative model that brings spot-level spatial data to single-cell resolution and imputes transcriptome-wide expression.	Python	Nature Communications 2023
XFuse	Bayesian deep generative model fusing histology and spot-level ST to infer super-resolved expression, including in unmeasured tissue.	Python	Nature Biotechnology 2022
GHIST	Multitask deep learning predicts single-cell-resolution spatial expression from H&E, trained on subcellular-resolution ST data.	Python	Nature Methods 2025
TESLA	Integrates histology with spot-level ST to impute pixel-level expression and annotate tumor and immune cell regions.	Python	Cell Systems 2023
ENVI (scENVI)	Variational model integrating scRNA-seq with spatial data to impute unimaged genes and infer COVET niche context for dissociated cells.	Python	Nature Biotechnology 2025
iSCALE	Predicts super-resolution expression for tissues larger than ST capture areas, using a large H&E image and several ST captures.	Python	Nature Methods 2025
TISSUE	Calibrated uncertainty estimates for imputed spatial gene expression, enabling more reliable downstream analyses.	Python	Nature Methods 2024
SpaGE	Aligns scRNA-seq and spatial data with domain adaptation (PRECISE), then predicts unmeasured genes by k-nearest-neighbor regression.	Python	Nucleic Acids Research 2020

Spatiotemporal & generative modeling

Dynamics across time points and generation of spatial data.

Tool	Description	Lang	Paper
moscot	Scalable optimal-transport framework mapping cells across time, space and modalities, including spatial alignment/mapping and spatiotemporal problems.	Python	Nature 2025
stVCR	Reconstructs continuous single-cell differentiation, proliferation, migration and slice alignment from time-series ST via unbalanced dynamical OT.	Python	Nature Methods 2026
Wasserstein Flow Matching (WFM)	Flow matching over families of distributions (Gaussians, point clouds); generates high-dimensional cellular microenvironments (niches) from ST data.	Python	ICML 2025
spaTrack	Optimal-transport trajectory inference combining expression and spatial distance, within single ST slices and across time-series slices.	Python	Cell Systems 2025
STORIES	Learns a differentiation potential (cell-fate landscape) from spatial transcriptomics time courses using fused Gromov–Wasserstein optimal transport.	Python	Nature Methods 2026
NicheFlow	Flow-matching generative model predicting how cellular microenvironments (cell states plus coordinates) evolve across time-resolved ST slices.	Python	NeurIPS 2025
STT (spatial transition tensor)	Learns a 4D transition tensor from mRNA splicing and spatial data to map multistable attractors and spatial state transitions.	Python	Nature Methods 2024
DeST-OT	Semi-relaxed optimal transport aligns ST slices from developmental timepoints, inferring per-spot growth and migration.	Python	Cell Systems 2025
GenOT	Graph contrastive learning plus fused Gromov–Wasserstein barycenter interpolation generates intermediate slices and integrates cross-platform ST data. (Disclosure: by the list maintainer.)	Python	Genome Biology 2026

Visualization & interactive exploration

Viewers for large spatial and single-cell datasets.

Tool	Description	Lang	Paper
CZ CELLxGENE (Annotate / Explorer)	No-code interactive explorer for single-cell datasets: embeddings, gene expression, subsetting and annotation.	Python/JS	Nucleic Acids Research 2025
Vitessce	Web framework for coordinated multiview visualization of multimodal and spatial single-cell data; usable from Jupyter and R.	JS/TS	Nature Methods 2025
iSEE	Interactive Shiny explorer for SummarizedExperiment/SingleCellExperiment objects with linked, customizable panels and reproducible code export.	R	F1000Research 2018
Cirrocumulus	Scalable web viewer for embeddings, dot plots, heatmaps and collaborative cell annotation of h5ad, Seurat, 10x and spatial data.	Python/JS	Nature Methods 2020
napari-spatialdata	napari plugin to interactively view and annotate SpatialData objects: images, labels, points, shapes and tables.	Python	Nature Methods 2025
spatialdata-plot	Static matplotlib-based plotting of SpatialData images, labels, points and shapes through a chainable API.	Python	Nature Methods 2025
TissUUmaps	Browser-based viewer, hosted or local, for exploring millions of spatial data points over tissue images and sharing views.	JS/TS	Heliyon 2023
ShinyCell / ShinyCell2	R packages that turn single-cell objects (ShinyCell2 also spatial, scATAC, CITE-seq) into shareable Shiny web apps.	R	Bioinformatics 2021
WebAtlas	Pipeline that turns single-cell and spatial datasets into interactive, Vitessce-based web atlases.	Python	Nature Methods 2025
Xenium Explorer (10x Genomics)	Desktop app for interactively exploring Xenium in situ data: transcripts, cell segmentation, images and clusters.	Desktop app
Loupe Browser (10x Genomics)	Desktop app for interactive exploration of 10x Chromium single-cell and Visium/Visium HD spatial data.	Desktop app

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🧬 Single-Cell Foundations

Single-cell frameworks & data structures

The ecosystems most spatial tools build on.

Tool	Description	Lang	Paper
Seurat	Widely used R toolkit for single-cell QC, normalization, clustering, differential expression, integration, multimodal and spatial analysis.	R	Nature Biotechnology 2024
Scanpy	Scalable Python toolkit for single-cell analysis on AnnData: preprocessing, clustering, embeddings, differential expression, PAGA and plotting.	Python	Genome Biology 2018
scvi-tools	PyTorch library of probabilistic deep generative models (scVI, scANVI, totalVI and more) for integration, annotation and multimodal analysis.	Python	Nature Biotechnology 2022
AnnData	Python annotated data matrix (cells × features with metadata, layers, embeddings); defines the .h5ad/zarr formats used across scverse.	Python	Journal of Open Source Software 2024
sceasy	Converts between Seurat, SingleCellExperiment, AnnData and Loom objects from R, using reticulate and Python anndata/loompy.	R
rapids-singlecell	GPU-accelerated, largely Scanpy-compatible single-cell analysis on AnnData using CuPy/RAPIDS; includes selected Squidpy, decoupler and pertpy functions.	Python	arXiv 2026 (preprint)
BPCells	Bitpacked, disk-backed sparse matrices and streaming algorithms for scalable scRNA-seq and scATAC-seq analysis in R; usable within Seurat v5.	R/C++	bioRxiv 2025 (preprint)
MuData / muon	MuData container (.h5mu) for multimodal data plus muon toolkit for ATAC, protein and multi-omic integration (MOFA+, WNN).	Python	Genome Biology 2022
zellkonverter	Converts between AnnData/.h5ad files and Bioconductor SingleCellExperiment objects, using a managed Python environment (basilisk) or native R reader.	R
anndataR	Native R reading/writing of .h5ad and zarr AnnData files, with conversion to SingleCellExperiment and Seurat; no Python needed.	R	Bioinformatics 2026
scater	Bioconductor toolkit for single-cell QC, visualization and dimensionality reduction on SingleCellExperiment objects.	R	Bioinformatics 2017
SingleCellExperiment	Core Bioconductor S4 container for single-cell data, used by scater, scran, batchelor and most Bioconductor single-cell packages.	R	Nature Methods 2020

Raw data processing

From reads to count matrices.

Tool	Description	Lang	Paper
STARsolo	Single-cell mode of the STAR aligner; Cell Ranger-like barcode/UMI counting for many protocols, with spliced/unspliced (velocity) output.	C++	bioRxiv 2021 (preprint)
Cell Ranger	Official 10x Genomics pipelines for Chromium data: alignment, barcode/UMI counting, cell calling, Feature Barcode and V(D)J analysis.	Rust	Nature Communications 2017
nf-core/scrnaseq	Nextflow best-practice pipeline for 10x scRNA-seq: simpleaf, STARsolo, kallisto\|bustools or Cell Ranger, plus CellBender filtering and MultiQC.	Nextflow
zUMIs	Pipeline for UMI and plate-based scRNA-seq (including Smart-seq3): STAR mapping, exon/intron counting, barcode detection and UMI collapsing.	R	GigaScience 2018
alevin-fry / simpleaf	Fast, memory-frugal scRNA-seq quantification from piscem/salmon mappings, with spliced/unspliced/ambiguous (USA) counting; simpleaf wraps the workflow.	Rust	Nature Methods 2022
kallisto \| bustools (kb-python)	Wraps kallisto pseudoalignment and bustools into one-command scRNA-seq preprocessing; supports many technologies, single-nucleus and RNA-velocity workflows.	Python	Nature Biotechnology 2021

Quality control

Ambient RNA, doublets and low-quality cells.

Tool	Description	Lang	Paper
DoubletFinder	Seurat-based doublet detection comparing each cell's neighborhood with simulated artificial doublets (pANN score).	R	Cell Systems 2019
CellBender	Deep generative model that removes ambient RNA and barcode-swapping background from raw droplet count matrices and calls cells.	Python	Nature Methods 2023
SoupX	Estimates the ambient-RNA ('soup') profile from empty droplets and removes the contamination from each cell's counts.	R	GigaScience 2020
scDblFinder	Fast doublet detection training gradient-boosted trees on real cells versus simulated doublets; handles multiple samples and scATAC-seq.	R	F1000Research 2022
Scrublet	Python doublet detection scoring each cell by k-NN similarity to simulated doublets built from random pairs of observed cells.	Python	Cell Systems 2019
Solo	Semi-supervised scVI-based classifier separating singlets from simulated doublets. Maintained in scvi-tools (original repo archived).	Python	Cell Systems 2020
DecontX	Bayesian model that estimates and removes per-cell ambient RNA contamination from cluster-level profiles; no empty droplets required.	R	Genome Biology 2020
DropletUtils (EmptyDrops)	Bioconductor utilities for droplet data: EmptyDrops cell calling, barcode-rank knee detection, swapped-barcode removal and 10x I/O.	R	Genome Biology 2019
miQC	Mixture model of mitochondrial fraction and genes detected that sets adaptive, data-driven cell-filtering thresholds instead of fixed cutoffs.	R	PLOS Computational Biology 2021

Normalization & feature selection

Tool	Description	Lang	Paper
sctransform	Regularized negative binomial regression; Pearson residuals give normalized, variance-stabilized UMI data (Seurat's SCTransform).	R	Genome Biology 2019
scran	Pooling-based (deconvolution) size factors for normalization, plus variance modeling for HVG selection and marker detection.	R	Genome Biology 2016
Analytic Pearson residuals	Closed-form Pearson residuals from a fixed-overdispersion negative binomial model for UMI normalization and HVG selection; implemented in Scanpy.	Python	Genome Biology 2021
Feature selection benchmark (Zappia et al.)	Benchmark of 20+ feature-selection methods for scRNA-seq integration and query mapping; finds highly variable gene selection effective.	Python/R	Nature Methods 2025
scry	Multinomial-model tools: binomial-deviance feature selection, null residuals and GLM-PCA dimensionality reduction on raw UMI counts.	R	Genome Biology 2019
transformGamPoi	Variance-stabilizing transformations for UMI counts: acosh, shifted log, Pearson and randomized-quantile residuals.	R	Nature Methods 2023

Integration, batch correction & reference mapping

Tool	Description	Lang	Paper
scVI	Variational autoencoder for raw counts conditioned on batch; its latent space is used for integration, normalization and differential expression. Part of scvi-tools.	Python	Nature Methods 2018
scANVI	Semi-supervised scVI extension that uses available cell-type labels for label-aware integration and label transfer to unannotated cells. Part of scvi-tools.	Python	Molecular Systems Biology 2021
sysVI	Conditional VAE with VampPrior and cycle-consistency for integrating systems with substantial batch effects (species, organoid vs tissue, cells vs nuclei). Part of scvi-tools.	Python	BMC Genomics 2025
Harmony	Iterative soft clustering in PCA space with cluster-specific linear corrections that remove dataset effects; fast and scalable.	R	Nature Methods 2019
LIGER (rliger)	Integrative non-negative matrix factorization (iNMF) learning shared and dataset-specific factors across samples, modalities and species.	R	Cell 2019
scArches	Transfer-learning 'architecture surgery' that maps query datasets onto pretrained reference models (e.g., scVI, scANVI) without sharing raw data.	Python	Nature Biotechnology 2022
scPoli	Generative model that learns sample embeddings and cell-type prototypes for population-level integration, reference mapping and label transfer. Part of scArches.	Python	Nature Methods 2023
Scanorama	Panorama-stitching integration that finds mutual nearest neighbors across all dataset pairs; handles heterogeneous collections with partially shared cell types.	Python	Nature Biotechnology 2019
BBKNN	Batch-balanced k-nearest-neighbor graph built per batch; fast graph-level correction feeding Scanpy clustering and UMAP.	Python	Bioinformatics 2020
Symphony	Compresses a Harmony-integrated reference so new query cells can be mapped and annotated in seconds without re-integration.	R	Nature Communications 2021
batchelor (MNN / fastMNN)	Bioconductor batch correction with mutual nearest neighbors (MNN, fastMNN) and related methods for SingleCellExperiment objects.	R	Nature Biotechnology 2018

Dimensionality reduction, clustering & visualization

Tool	Description	Lang	Paper
UMAP (umap-learn)	Manifold-learning dimensionality reduction (fuzzy topological graph); widely used for 2-D visualization of single-cell data.	Python	arXiv 2018 (preprint)
openTSNE	Fast, extensible t-SNE (FFT interpolation, Barnes-Hut) that can add new points to existing embeddings.	Python	Journal of Statistical Software 2024
leidenalg	Implementation of Leiden community detection, which guarantees well-connected communities; clustering backend for Scanpy's sc.tl.leiden.	Python	Scientific Reports 2019
PHATE	Diffusion-based potential-distance embedding that preserves local and global structure, highlighting continuous transitions and branches.	Python	Nature Biotechnology 2019
clustree	Plots clusterings at several resolutions as a tree, showing how cells move between clusters to guide resolution choice.	R	GigaScience 2018

Cell type annotation

Tool	Description	Lang	Paper
CellTypist	Automated annotation with logistic-regression classifiers and a library of curated pre-trained immune and tissue models.	Python	Science 2022
ScType	Fast, fully automated marker-based annotation scoring positive and negative markers from the ScType database.	R	Nature Communications 2022
CellAssign	Probabilistic model assigning cells to predefined types from known marker genes, without a reference dataset.	R	Nature Methods 2019
SingleR	Reference-based annotation correlating each cell with labelled reference profiles, refined by iterative fine-tuning.	R	Nature Immunology 2019
Azimuth	Web app and R package mapping query cells onto curated Seurat reference atlases to transfer labels.	R	Cell 2021
CellHint	Harmonises cell type labels across independently annotated datasets and uses them to guide integration.	Python	Cell 2023
popV	Ensemble of annotation algorithms with ontology-aware voting, giving consensus labels and per-cell certainty scores.	Python	Nature Genetics 2024

Differential expression & abundance

Tool	Description	Lang	Paper
Milo (miloR)	Differential abundance testing on overlapping kNN-graph neighbourhoods with negative binomial GLMs.	R	Nature Biotechnology 2022
MAST	Hurdle model for single-cell differential expression that adjusts for the cellular detection rate.	R	Genome Biology 2015
muscat	Multi-sample, multi-condition differential state analysis using pseudobulk (edgeR/DESeq2/limma) and mixed models.	R	Nature Communications 2020
scCODA	Bayesian compositional model detecting changes in cell type proportions relative to a reference cell type.	Python	Nature Communications 2021
Libra	One-function interface to many single-cell DE methods, including pseudobulk edgeR/DESeq2/limma and mixed models.	R	Nature Communications 2021
memento	Method-of-moments framework testing differences in mean expression, variability and gene correlation.	Python	Cell 2024
LEMUR	Latent embedding multivariate regression for cluster-free differential expression in multi-condition data.	R	Nature Genetics 2025
propeller (speckle)	Tests cell type proportion differences between groups using transformed proportions and linear models.	R	Bioinformatics 2022

Trajectory, pseudotime & RNA velocity

Tool	Description	Lang	Paper
PAGA	Graph abstraction of cluster connectivity giving topology-preserving maps for trajectory inference. Part of Scanpy.	Python	Genome Biology 2019
scVelo	RNA velocity with a dynamical model of transcriptional kinetics, plus latent time and velocity graphs.	Python	Nature Biotechnology 2020
Dynamo	Reconstructs continuous expression vector fields from RNA velocity (incl. metabolic labeling) for dynamics and in silico perturbation.	Python	Cell 2022
Monocle 3	Learns principal graphs to order cells in pseudotime and find genes varying along trajectories.	R	Nature 2019
CellRank	Markov-chain fate mapping from velocity, pseudotime, real time or other kernels; estimates fate probabilities and drivers.	Python	Nature Methods 2024
Slingshot	Infers lineages over clusters and fits simultaneous principal curves to compute per-lineage pseudotime.	R	BMC Genomics 2018
Palantir	Models differentiation as a Markov chain on diffusion maps to estimate pseudotime and terminal fate probabilities.	Python	Nature Biotechnology 2019
CytoTRACE 2	Interpretable deep learning that predicts each cell's absolute developmental potential (potency) from its expression profile.	R/Python	Nature Methods 2025
RegVelo	Couples RNA velocity with gene regulatory networks to model cell dynamics and predict effects of regulator perturbations.	Python	Cell 2026
dyno (dynverse)	Uniform interface to ~60 trajectory inference methods with method-selection guidelines, from the large TI benchmark.	R	Nature Biotechnology 2019
velocyto	Original RNA velocity: counts spliced/unspliced reads and extrapolates future transcriptional states.	Python	Nature 2018
Waddington-OT (wot)	Optimal transport over time-course scRNA-seq to infer ancestor–descendant couplings and fate trajectories.	Python	Cell 2019
MultiVelo	Extends RNA velocity with chromatin accessibility from single-cell multiome data to model gene regulation dynamics.	Python	Nature Biotechnology 2023
veloVI	Deep generative model of transcriptional dynamics for RNA velocity with uncertainty quantification.	Python	Nature Methods 2024

Gene regulatory networks

Tool	Description	Lang	Paper
SCENIC / pySCENIC	Infers TF regulons from co-expression pruned by cis-regulatory motif enrichment, then scores regulon activity per cell.	Python	Nature Methods 2017
CellOracle	Builds cell-state-specific GRNs using an ATAC-derived base network, then simulates TF perturbations in silico.	Python	Nature 2023
decoupler	Infers TF and pathway activities from prior-knowledge networks (e.g., CollecTRI, PROGENy) using multiple statistical methods.	Python	Bioinformatics Advances 2022
SCENIC+	Infers enhancer-driven GRNs (eRegulons) from paired or unpaired scRNA-seq and scATAC-seq using motif enrichment.	Python	Nature Methods 2023
LINGER	Infers gene regulatory networks from single-cell multiome data, using lifelong learning on large external bulk data.	Python	Nature Biotechnology 2025
Dictys	Infers cell-type-specific and dynamic GRNs along trajectories from scRNA-seq plus scATAC-seq using TF footprinting.	Python	Nature Methods 2023
Arboreto (GRNBoost2)	Scalable Dask-based GRN inference with GRNBoost2 and GENIE3; the co-expression step behind pySCENIC.	Python	Bioinformatics 2019

Cell–cell communication

Ligand–receptor inference from dissociated cells. For spatial methods, see Cell–cell communication & niches.

Tool	Description	Lang	Paper
NicheNet (nichenetr)	Prioritises sender ligands by their predicted regulatory effect on receiver-cell target genes using prior knowledge.	R	Nature Methods 2020
CellChat	Ligand–receptor database with cofactors; models communication probabilities and analyses signaling networks and pathways.	R	Nature Protocols 2025
CellPhoneDB	Curated ligand–receptor database including multi-subunit complexes, with statistical inference of interacting cell type pairs.	Python	Nature Protocols 2025
MultiNicheNet	Differential cell–cell communication for multi-sample, multi-condition designs, combining pseudobulk DE with NicheNet ligand activities.	R	bioRxiv 2023 (preprint)
Scriabin	Single-cell-resolution communication analysis without aggregation, enabling comparisons across samples and conditions.	R	Nature Biotechnology 2024
CellCall	Infers communication by combining ligand–receptor expression with downstream TF activity in receiving cells.	R	Nucleic Acids Research 2021
Tensor-cell2cell	Tensor decomposition of communication scores across samples or conditions to extract context-dependent communication patterns.	Python	Nature Communications 2022

Multi-omics & multimodal integration

Tool	Description	Lang	Paper
Seurat WNN	Weighted nearest neighbour analysis learning per-cell modality weights to jointly analyse RNA with protein or ATAC.	R	Cell 2021
totalVI	Deep generative model jointly modelling CITE-seq RNA and protein, with protein background correction and integration. Part of scvi-tools.	Python	Nature Methods 2021
MultiVI	Deep generative model integrating paired and unpaired scRNA-seq and scATAC-seq (optionally protein) into one latent space. Part of scvi-tools.	Python	Nature Methods 2023
scGLUE	Graph-linked unified embedding integrating unpaired multi-omics via prior regulatory graphs; also infers regulatory links.	Python	Nature Biotechnology 2022
ArchR	Scalable scATAC-seq analysis: QC, clustering, peak calling, motif deviations, scRNA integration and trajectories.	R	Nature Genetics 2021
Signac	Seurat extension for single-cell chromatin data: peaks, motifs, footprinting, peak–gene links and RNA integration.	R	Nature Methods 2021
MOFA+	Bayesian group factor analysis inferring interpretable latent factors shared across modalities and sample groups.	R/Python	Genome Biology 2020
SnapATAC2	Fast Rust-backed package for scATAC-seq and other single-cell omics using matrix-free spectral embedding.	Python	Nature Methods 2024
MaxFuse	Integrates modalities with weakly linked features (e.g., targeted protein vs RNA) via fuzzy-smoothed iterative co-embedding.	Python	Nature Biotechnology 2024

Perturbation analysis & modeling

Tool	Description	Lang	Paper
Mixscape (Seurat)	Classifies CRISPR-targeted cells as perturbed or escaping, then visualises perturbation-specific responses in pooled screens.	R	Nature Genetics 2021
GEARS	Graph neural network on a gene–gene knowledge graph predicting outcomes of unseen single and multi-gene perturbations.	Python	Nature Biotechnology 2024
scGen	VAE with latent vector arithmetic predicting perturbation responses in unseen cell types or species.	Python	Nature Methods 2019
pertpy	scverse framework for perturbation studies: Milo, scCODA, Mixscape, perturbation distances, response spaces and dataset loaders.	Python	Nature Methods 2026
scPerturb	Harmonised resource of single-cell perturbation datasets with energy-statistics tools for comparing perturbation effects.	Python	Nature Methods 2024
CellOT	Neural optimal transport learning maps from control to perturbed single-cell states to predict per-cell responses.	Python	Nature Methods 2023
CPA	Compositional perturbation autoencoder disentangling perturbation, dose and covariates to predict unseen combinations.	Python	Molecular Systems Biology 2023
SCEPTRE	Calibrated, resampling-based association testing between perturbations and gene expression in single-cell CRISPR screens.	R	Genome Biology 2024

Copy number, clonality & immune repertoire

Tool	Description	Lang	Paper
inferCNV	Infers large-scale copy number changes in tumour cells by comparing smoothed expression against reference normal cells.	R
scRepertoire	R toolkit for single-cell TCR/BCR clonotype quantification, diversity and overlap, integrated with Seurat/SingleCellExperiment.	R	PLOS Computational Biology 2025
CopyKAT	Bayesian segmentation of scRNA-seq to infer copy number, separate aneuploid tumour from diploid cells, and find subclones.	R	Nature Biotechnology 2021
scirpy	scverse toolkit for single-cell TCR/BCR data: clonotype definition, expansion, diversity and integration with transcriptomes.	Python	Bioinformatics 2020
Numbat	Haplotype-aware CNV inference combining allele imbalance and expression, reconstructing tumour clonal phylogenies.	R	Nature Biotechnology 2023
Dandelion	Single-cell BCR/TCR V(D)J analysis: reannotation, clonotype networks and V(D)J-informed developmental trajectories.	Python	Nature Biotechnology 2024
SCEVAN	Variational segmentation of scRNA-seq to call copy number, classify malignant cells and resolve clonal substructure.	R	Nature Communications 2023

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🤖 AI & Foundation Models

Single-cell foundation models

Large models pretrained on millions of cells.

Tool	Description	Lang	Paper
scGPT	Generative pretrained transformer trained on 33M+ human cells; fine-tuned for annotation, batch integration, perturbation prediction and GRN inference.	Python	Nature Methods 2024
State	Arc Institute virtual-cell model predicting perturbation responses over cell sets; trained on ~170M observational and 100M+ perturbed cells.	Python	Cell 2026
scFoundation	100M-parameter asymmetric transformer pretrained on 50M+ human cells covering ~20k genes, using read-depth-aware masked pretraining.	Python	Nature Methods 2024
scBERT	BERT-style transformer pretrained on ~1.1M unlabeled PanglaoDB cells, then fine-tuned for cell type annotation.	Python	Nature Machine Intelligence 2022
UCE (Universal Cell Embeddings)	Zero-shot, species-agnostic cell embeddings using protein-language-model gene tokens; built a 36M-cell atlas spanning eight species.	Python	Nature 2026
SCimilarity	Metric-learning model for fast cell-similarity search; queries a 23.4M-cell atlas from 412 human scRNA-seq studies.	Python	Nature 2025
TranscriptFormer	Generative cross-species model (CZI) trained on up to 112M cells from 12 species spanning 1.53 billion years of evolution.	Python	Science 2026
scPRINT	Transformer pretrained on 50M+ CELLxGENE cells, designed for gene network inference plus denoising, batch correction and label prediction.	Python	Nature Communications 2025
GeneCompass	Cross-species model pretrained on ~100M human and mouse cells, integrating prior knowledge such as GRNs and promoter sequences.	Python	Cell Research 2024
CellFM	800M-parameter RetNet-style model pretrained on ~100M human cells using MindSpore; annotation, perturbation and gene-function tasks.	Python	Nature Communications 2025
CellPLM	Cell language model treating cells as tokens and tissues as sentences; pretraining includes spatial data to learn cell-cell relations.	Python	ICLR 2024
scMulan	368M-parameter generative language model pretrained on 10M cells with metadata; zero-shot annotation, integration and conditional generation.	Python	RECOMB (LNCS) 2024
scLong	Billion-parameter model pretrained on 48M cells, attending over all ~28k human genes to capture long-range gene context.	Python	Nature Communications 2026
Geneformer	Transformer using rank-value gene encoding; V1 pretrained on ~30M human cells, V2 on ~104M; supports in silico perturbation.	Python	Nature 2023

Spatial & multimodal foundation models

Models that learn from spatial context, histology or several modalities.

Tool	Description	Lang	Paper
Nicheformer	Transformer pretrained on SpatialCorpus-110M (dissociated and spatial human/mouse cells); transfers spatial context to scRNA-seq data.	Python	Nature Methods 2025
Novae	Self-supervised graph attention model trained on ~30M spatial cells across 18 tissues; zero-shot spatial domains and batch correction.	Python	Nature Methods 2025
Loki (OmiCLIP)	Contrastive H&E-transcriptomics model trained on 2.2M Visium image-expression pairs; supports alignment, annotation, deconvolution and expression prediction.	Python	Nature Methods 2025
scGPT-spatial	scGPT continually pretrained on SpatialHuman30M (Visium, Visium HD, MERFISH, Xenium) with mixture-of-experts decoders for spatial tasks.	Python	bioRxiv 2025 (preprint)
SToFM	Multi-scale spatial transcriptomics model using an SE(2) Transformer; pretrained on SToCorpus-88M (88M cells, six technologies).	Python	ICML 2025
STPath	Generative model predicting spatial expression of 38,984 genes from whole-slide H&E images; trained on HEST-1k and STimage-1K4M.	Python	npj Digital Medicine 2025
CELLama	Turns cell expression and metadata into sentences embedded by a language model; cell typing and spatial-context analysis.	Python	Advanced Science 2026
SpatialFormer	CNN-transformer pretrained on 17M Xenium cells, learning subcellular transcript layout and niche context; annotation, batch correction, co-localization.	Python	Nature Computational Science 2026

LLMs & agents

Language models and agents that annotate cells or run analyses.

Tool	Description	Lang	Paper
Biomni	General-purpose biomedical agent combining LLM reasoning, retrieval and code execution over curated tools, databases and protocols.	Python	Science 2026
Cell2Sentence (C2S-Scale)	Encodes cells as ranked gene-name sentences for LLM training; C2S-Scale extends this to Gemma-2 models up to 27B parameters.	Python	ICML 2024
GenePT	Gene and cell embeddings built from GPT-3.5 text embeddings of gene descriptions, without expression-based pretraining.	Python	Nature Biomedical Engineering 2025
CellVoyager	LLM agent that autonomously proposes and runs new scRNA-seq analyses in Jupyter notebooks, re-analyzing published datasets.	Python	Nature Methods 2026
GPTCelltype	R package and study showing GPT-4 annotates cell types from marker genes, agreeing well with manual annotations.	R	Nature Methods 2024
CellWhisperer	Contrastive transcriptome-text embedding trained on ~1M RNA-seq profiles plus an LLM for chat-based exploration in CELLxGENE.	Python	Nature Biotechnology 2025
SpatialAgent	LLM agent for spatial biology: gene-panel design, cell annotation, cell-cell communication analysis and hypothesis generation.	Python	bioRxiv 2025 (preprint)
CASSIA	Multi-agent LLM framework for reference-free, interpretable cell type annotation with validation and quality scoring.	Python	Nature Communications 2026

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📊 Benchmarks & Evaluation

Benchmarks & evaluation

Independent comparisons to consult before picking a method.

Tool	Description	Lang	Paper
Open Problems in Single-Cell Analysis	Living, community-guided benchmarking platform with formalized single-cell tasks, datasets, metrics and public leaderboards.	Python/R	Nature Biotechnology 2025
scIB	Benchmark of 68 method-preprocessing combinations on 13 atlas-level integration tasks with 14 metrics; reusable scib metrics package.	Python	Nature Methods 2022
dynbenchmark	Comparison of 45 trajectory inference methods on 110 real and 229 synthetic datasets; underlies the dynverse toolkit.	R	Nature Biotechnology 2019
BEELINE	Framework benchmarking GRN inference from scRNA-seq using synthetic networks, curated Boolean models and experimental datasets.	Python	Nature Methods 2020
Virtual Cell Challenge	Arc Institute's annual competition predicting CRISPRi perturbation responses; 2026 edition tests zero-shot transfer to unseen cell lines.	Python	Cell 2025
SpatialBenchmarking (Li et al.)	Benchmark of 16 methods integrating scRNA-seq with spatial data for gene imputation and spot deconvolution (45 paired datasets).	Python	Nature Methods 2022
scPerturBench	Benchmark of 27 genetic and chemical perturbation-response methods on 29 datasets, testing generalization to unseen contexts and perturbations.	Python	Nature Methods 2026
Linear baselines for perturbation prediction	Shows foundation and deep-learning perturbation models do not beat simple linear/additive baselines on single and double perturbations.	R	Nature Methods 2025
Zero-shot evaluation of single-cell foundation models	Shows zero-shot scGPT and Geneformer embeddings can underperform HVG selection and scVI for cell clustering and batch integration.	Python	Genome Biology 2025
Systema	Evaluation framework separating perturbation-specific effects from systematic control-vs-perturbed variation that inflates standard metrics.	Python	Nature Biotechnology 2026
SDMBench (spatial clustering benchmark)	Benchmark of 13 spatial clustering/domain methods on 34 spatial transcriptomics datasets; accuracy, continuity, marker detection, scalability.	Python	Nature Methods 2024
PertEval-scFM	Standardized framework testing whether zero-shot scFM embeddings improve perturbation-effect prediction; finds limited gains over simple baselines.	Python	ICML 2025
Spotless	Reproducible Nextflow benchmark of spatial deconvolution methods on simulated and real datasets.	R	eLife 2024
BenchmarkST	Benchmark of clustering, slice alignment and integration methods for spatial transcriptomics across many datasets.	Python	Genome Biology 2024

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📦 Data

Atlases, data portals & databases

Resource	Description	Paper
HEST-1k	1,000+ spatial transcriptomics samples paired with H&E whole-slide images, plus loading library and expression-prediction benchmark.	NeurIPS 2024
Tabula Muris / Tabula Muris Senis	Single-cell transcriptomic atlases of 20 mouse organs (Tabula Muris) and of tissue ageing (Tabula Muris Senis).	Nature 2018
CZ CELLxGENE Discover & Census	Curated, standardized single-cell data platform with web exploration and the Census API for programmatic Python/R access.	Nucleic Acids Research 2025
Allen Brain Cell Atlas (ABC Atlas)	Allen Institute platform to explore and download brain cell-type atlases: whole mouse brain scRNA-seq/MERFISH, human brain and more.	Nature 2023
spatialLIBD	R/Bioconductor package and web apps to access and explore LIBD human brain Visium datasets, such as DLPFC.	BMC Genomics 2022
Broad Single Cell Portal	Self-service Broad portal for sharing, visualizing and downloading single-cell and spatial studies with interactive gene views.	bioRxiv 2023 (preprint)
Tabula Sapiens	Multi-organ human single-cell transcriptomic reference atlas; Tabula Sapiens 2.0 spans ~1.1 million cells from 28 tissues.	Science 2022
UCSC Cell Browser	Web viewer hosting hundreds of published single-cell datasets, plus open-source tools to build your own browser.	Bioinformatics 2021
Human Cell Atlas Data Portal	Official repository for Human Cell Atlas data: browse and download raw sequencing data, metadata and expression matrices.	eLife 2017
DISCO	Database of deeply integrated human single-cell omics data, with harmonized metadata, tissue atlases, and online annotation and integration tools.	Nucleic Acids Research 2022
Single Cell Expression Atlas (EMBL-EBI)	EMBL-EBI resource reanalysing public single-cell RNA-seq datasets with standardized pipelines across many species, including marker genes.	Nucleic Acids Research 2024
CellMarker 2.0	Manually curated database of human and mouse cell-type markers, with web tools for single-cell data analysis.	Nucleic Acids Research 2023
PanglaoDB	Database of uniformly processed mouse and human scRNA-seq samples and curated cell-type marker genes.	Database (Oxford) 2019
SODB (Spatial Omics DataBase)	Spatial omics database with >2,400 experiments from >25 technologies, unified downloads and interactive analysis modules.	Nature Methods 2023
STOmicsDB	CNGB spatial transcriptomics hub for data archiving and sharing, with curated, annotated public datasets and visualization.	Nucleic Acids Research 2024
HuBMAP Data Portal	NIH Human BioMolecular Atlas Program portal for single-cell, spatial and imaging maps of healthy human tissues.	Nature 2019
HTAN Data Portal	NCI Human Tumor Atlas Network portal with single-cell, spatial and imaging data charting cancer transitions.	Cell 2020
10x Genomics Datasets	Free example datasets from 10x Chromium, Visium (including HD) and Xenium platforms, with processed outputs.

Simulation

Synthetic data with known ground truth for benchmarking.

Tool	Description	Lang	Paper
Splatter	Bioconductor package simulating scRNA-seq counts with groups, paths and batches; offers a common interface to other simulators.	R	Genome Biology 2017
scDesign3	Fits interpretable statistical models to real data to generate realistic synthetic single-cell and spatial omics data.	R	Nature Biotechnology 2024
SERGIO	Python simulator generating single-cell expression from user-defined gene regulatory networks, at steady state or along differentiation.	Python	Cell Systems 2020
dyngen	Multi-modal simulator of single cells undergoing dynamic processes, driven by gene regulatory networks, for benchmarking methods.	R	Nature Communications 2021
scMultiSim	Simulates single-cell multi-omics and spatial data guided by gene regulatory networks and cell–cell interactions.	R	Nature Methods 2025
scCube	Python package for reproducible, platform-diverse simulation of spatial transcriptomics with customizable cell-type spatial patterns.	Python	Nature Communications 2024
SymSim	R package simulating scRNA-seq with extrinsic, intrinsic (kinetic) and technical variation, plus tree-based population structure.	R	Nature Communications 2019
SRTsim	R framework for reproducible spatially resolved transcriptomics simulation that preserves spatial expression patterns, for benchmarking.	R	Genome Biology 2023

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awesome-single-cell – The largest community list of single-cell software and data resources.
awesome_spatial_omics – Tools and notes for spatial omics.
awesome-spatial-omics – Spatial omics technologies and methods.
awesome-single-cell-foundation – Papers on single-cell foundation models.

Contributing

Contributions are welcome! Please read the contributing guide first. If you spot a dead link, an archived repository or a wrong paper, please open an issue.

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wrab12/awesome-spatial-transcriptomics

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README

Awesome Spatial Transcriptomics

Contents

🧭 Start Here

Best-practice guides & books

Courses & hands-on tutorials

Key reviews

🔬 Spatial Technologies

Spatial technologies

📍 Spatial Transcriptomics Analysis

Spatial frameworks

Cell segmentation & preprocessing

Spatially variable genes

Spatial domains & clustering

Deconvolution & single-cell mapping

Alignment, integration & 3D reconstruction

Cell–cell communication & niches

Super-resolution, imputation & histology-to-expression

Spatiotemporal & generative modeling

Visualization & interactive exploration

🧬 Single-Cell Foundations

Single-cell frameworks & data structures

Raw data processing

Quality control

Normalization & feature selection

Integration, batch correction & reference mapping

Dimensionality reduction, clustering & visualization

Cell type annotation

Differential expression & abundance

Trajectory, pseudotime & RNA velocity

Gene regulatory networks

Cell–cell communication

Multi-omics & multimodal integration

Perturbation analysis & modeling

Copy number, clonality & immune repertoire

🤖 AI & Foundation Models

Single-cell foundation models

Spatial & multimodal foundation models

LLMs & agents

📊 Benchmarks & Evaluation

Benchmarks & evaluation

📦 Data

Atlases, data portals & databases

Simulation

Related lists

Contributing

Star History

Similar repos

wrab12/awesome-spatial-transcriptomics

See what people are saying

README

Awesome Spatial Transcriptomics

Contents

🧭 Start Here

Best-practice guides & books

Courses & hands-on tutorials

Key reviews

🔬 Spatial Technologies

Spatial technologies

📍 Spatial Transcriptomics Analysis

Spatial frameworks

Cell segmentation & preprocessing

Spatially variable genes

Spatial domains & clustering

Deconvolution & single-cell mapping

Alignment, integration & 3D reconstruction

Cell–cell communication & niches

Super-resolution, imputation & histology-to-expression

Spatiotemporal & generative modeling

Visualization & interactive exploration

🧬 Single-Cell Foundations

Single-cell frameworks & data structures

Raw data processing

Quality control

Normalization & feature selection

Integration, batch correction & reference mapping

Dimensionality reduction, clustering & visualization

Cell type annotation