Closed nangosyah closed 2 months ago
Hey @nangosyah
Unfortunately I don't have a generalized linear model implemented for crispr_screen
where you can account for multiple variables and their interactions.
However, you can perhaps run DESeq2
or edgeR
with your specific design for the differential abundance analysis and then use crispr_screen agg
to aggregate the p-values at a gene level for the sgRNAs on your chosen contrast.
For visualization you can check out my tool screenviz
Hello,
I'm trying to use this implementation to do some analysis on pooled KO-CRISPR experiment with 10 samples divided in two groups: control and treatment. For each sample I have the amount of guideRNA at T0 and at T12. I want to find which genes are differentially expressed.
Is there a way I can account for time in the model and also visualise the results from the work flow.
Thanks