Computational identification of clonal cells in single-cell CRISPR screens

Overview

This repository described the scripts for identifying clones in single-cell CRISPR screens with multiplexed sgRNA barcodes.

Requirement

• Python (3.6 +)
• Numpy (1.16 +)
• Pandas (0.25 +)
• Scipy (1.1 +)
• Matplotlib (3.3 +)

Original Fastq Files

GEO accession: GSE185995

Pipelines

Step 1: Mapping and pre-processing

• Map the transcriptome libraries.
• Map the sgRNA libraries and filter.
• Filter out the experimental doublet cells.
• Generate a pandas dataframe of sgRNA library (rows: sgRNA sequence / columns: cell IDs) and save as python pickle file.
• Example file can be found in the supplementary file session of GSE185995: GSE185995_sgRNA_df_adj_regex.pkl.gz

Step 2: Group clones analysis

• Perform the group clones analysis on shell.

Step 3: Clonality visualization

• Read the clonal dictionary file with jupyter lab and visualize clonality.

How to cite

Wang, Y., Xie, S., Armendariz, D., Hon, GC. Computational identification of clonal cells in single-cell CRISPR screens. BMC Genomics 23, 135 (2022) Link to paper

Contributors

• First Author: Yihan Wang [email protected]
• Corresponding Author: Gary Hon [email protected]