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proxbias

Code to support the publication "High-resolution genome-wide mapping of chromosome-arm-scale truncations induced by CRISPR-Cas9 editing". The preprint is on bioRxiv here

Installation

This package is installable via Nexus.

pip install proxbias

Notebooks

Notebooks to reproduce plots from public datasets are included in the notebooks directory. Note that this doesn't include rxrx3 for IP reasons at this time.

  • cpg0016_loading.ipynb - Load the JUMP CP data, apply PCA and proximity bias correction and save data locally.
  • cpg0016_plots.ipynb - Create whole-genome plots from cpg0016, calculate Brunner-Munzel statistics and make bar plots.
  • shinyDepMap_benchmark.ipynb - Load DepMap 19Q3 data and create plots showing an enrichment for within-chromosome arm relationships.
  • DepMap_PB_Drivers.ipynb - Use DepMap 22Q4 data to look at differential proximity bias when TP53 and other genes are wild-type vs loss/gain of function.
  • DepMap_22q4_vs_23q2.ipynb - Generate whole-genome plots and Brunner-Munzel probability plots for DepMap 22Q4 and 23Q2 data.
  • scPerturb_tables_heatmaps.ipynb - Load scRNASeq datasets from scPerturb, run infercnv, compute chromosomal loss, generate result tables, and plot infercnv heatmaps for cells with specific loss.

TODO:

  • Code to search DepMap for drivers of proximity bias

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