Loki

Building on OmiCLIP, a visual–omics foundation model designed to bridge omics data and hematoxylin and eosin (H&E) images, we developed the Loki platform, which has five key functions: tissue alignment using ST or H&E images, cell type decomposition of ST or H&E images using scRNA-seq as a reference, tissue annotation of ST or H&E images based on bulk RNA-seq or marker genes, ST gene expression prediction from H&E images, and histology image–transcriptomics retrieval.

Please find our preprint here.

User Manual and Notebooks

You can view the Loki website and notebooks locally by dobule clicking the ./website/index.html file. It should show up in your default browser. This README provides a quick overview of how to set up and use Loki.

Source Code

All source code for Loki is contained in the ./src/loki directory.

Installation (It takes about 5 mins to finish the installation on MacBook Pro)

1. Create a Conda environment:

   conda create -n loki_env python=3.9
   conda activate loki_env
   

2. Navigate to the Loki source directory and install Loki:

   cd ./src
   pip install .
   

Usage

Once Loki is installed, you can import it in your Python scripts or notebooks:

import loki.preprocess
import loki.utils
import loki.plot

import loki.align
import loki.annotate
import loki.decompose
import loki.retrieve
import loki.predex

STbank

The ST-bank database are avaliable from Google Drive link.

The links_to_raw_data.xlsx file includes the source paper names, doi links, and download links of the raw data. The text.csv file includes the gene sentences with paired image patches. The image.tar.gz includes the image patches.

Pretrained weights

The pretrained weights are avaliable in Loki/checkpoint.pt

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license: bsd-3-clause