We present PerturBase, the most comprehensive database designed for the analysis and visualization of single-cell perturbation datasets (http://www.perturbase.cn/). PerturBase collects 122 datasets from 46 publicly research studies, covering 115 single-modal and 7 multi-modal datasets that include 24,254 genetic and 230 chemical perturbations from about approximately 5 million cells.
To demonstrate the readability, reusability, and reproducibility of our single-cell perturbation data preprocess and analysis workflow, we provided a demo case.
R_env.yaml
, Python_env.yaml
are the R_env
and Python_env
packages used in the pipeline_bash_files
. Please first install them in your environment.
Due to the size exceeding GitHub's limitations, demo data is hosted at Figshare. To run through our standard preprocess workflow, please execute the following commands with the demo data.
Specifically, for RNA-seq and ATAC-seq, please organize the files as follows,
Demo_data
├── RNA
│ ├── raw.h5ad
│
│
├── ATAC
├── fragment.tsv.gz
├── fragment.tsv.gz.tbi
├── cbc_perturbation_dict.tsv
Here is where we store the code for processing workflows of different types of raw data. You can use this code to replicate our results. Especially for our demo data:
For ATAC-seq fragment data set,
bash ATAC_fragment_all.sh /path_to_your_file/Demo_data/ATAC Hs
For RNA-seq data set,
bash RNA_all.sh /path_to_your_file/Demo_data/RNA Hs
Before executing the script, please replace Python_env
, R_env
, Script_base_path
, msigdb_Signature_path
, etc., with the paths on your local machine.
Scripts that is invoked by the main program, i.e, pipeline_bash_files.
Molecular signatures used in PerturBase
This manuscript reproduce_the_result_of_mixscape.py is the code for reproducing the extended Data of Fig.9a of Characterizing the molecular regulation of inhibitory immune checkpoints with multimodal single-cell screens. We use the manuscript evaluate_the_impact_of_hvg.py to evaluate the impact of the selection of hvg in data preprocessing on the perturbation-specific differentially expressed genes.
Any question is welcome in the issue.
Zhiting Wei, Duanmiao Si, Qi Liu et al. PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization, 2024.