Hi everyone! I’m an undergraduate doing research based on gene expression and CRISPR gene effect data in Depmap. When I combine the expression and gene effect data together, I found various genes that are zero expressed in most tumor cell lines, but have a wide range of gene effect. For example, gene USP17L10 is not expressed in most tumor cell lines, but have a gene effect range from -1 to 0.6. How can we explain this? Thank you ~
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Hi Jialin, like any screen, Achilles has a false positive rate. You can control false discovery by using the probability of gene dependency (CRISPRGeneDependency - sometimes labeled with “PR” in portal tools). However, in the case of USP17L10 specifically, I think the expression profile is wrong based on its expected gene functions, which imply ubiquitous expression.
Thank you for your explanation! I wonder if you have removed batch effect in Gene expression TPM data? Because these days I am aggregating gene expression data from different sources, the PCA results lead me to remove batch effects using ComBat() in sva package. Then I got TPM below zero in some genes. It is confusing ~
