How to interpret CERES gene scores for genome wide CRISPR-Cas9 knockout screens?

Question

[patelk26]

Hello,

I am using Achilles dataset (DepMap Public 19Q2) which contains the results of genome-scale CRISPR knockout screen to study the effect of genes in survival and proliferation of certain cancer cell lines. I have a data matrix which contains scores for 17,634 genes across 563 cell lines. I do not understand how to interpret these scores, any help on how to interpret it would be really appreciated.

Thanks!

Answer 1

[patelk26]

https://www.biorxiv.org/content/10.1101/160861v1

The above paper about CERES was helpful in explaining CERES as a computation method to estimate gene dependency levels which accounts for the copy number specific effect (regions with high CN causes sequence-independent DNA damage and G2 cell-cycle arrest) and variable sgRNA activity. From what I understand, a more negative CERES score indicates depletion of the gene in that cell line, indicating that it is an essential gene for cell viability and a positive score indicates that it is more enriched.