scCAPE Data

Description

We have conducted a computational analysis of single cell genetic perturbation experiments. No new experimental data is generated duirng our study. Here we post analysis results of several Perturb-seq/CROP-seq datasets. 'Dixit2016_K562cells.zip' The zipped file contains two dictionary files, 'tau_factor_mean_all_dict.pkl' and 'tau_q_val_factor_all_dict.pkl'. In these dictionaries, the keys represent perturbations, and the values are cell-by-factor arrays of perturbation effect estimations and the corresponding q-values for each factor in each cell. 'SM2018_Tcells.zip' The zipped file contains two dictionary files, 'tau_factor_mean_all_dict.pkl' and 'tau_q_val_factor_all_dict.pkl'. In these dictionaries, the keys represent perturbations, and the values are cell-by-factor arrays of perturbation effect estimations and the corresponding q-values for each factor in each cell. 'Norman2019.zip' The zipped file contains two dictionary files, 'tau_factor_mean_all_dict.pkl' and 'tau_q_val_factor_all_dict.pkl'. In these dictionaries, the keys represent perturbations, and the values are cell-by-factor arrays of perturbation effect estimations and the corresponding q-values for each factor in each cell. These CSV files contain the results of a specific perturbation on a specific factor, and the proportion of cells that are significant in each type of genetic interaction (BF: buffering; DM: dominant; SY: synergistic; epiA: epistasis A; epiB: epistasis B) for each factor.

Steps to reproduce

This is a computational work, and the source code to generate data is available at https://github.com/zcfu21/scCAPE.

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