I have a question about scores that are given in Crispr (Avana) Public 20Q3. The gene of my interest gives scores from -1.3 to 0.36 in different cell lines after Crispr knockout. What these scores technically mean? Should I consider all cell lines below 0 as affected (=showing growth problems)? And those giving scores above 0 as feeling better after knockout (growing faster=not negativelly affected)?
And when I look for biomarkers which classify lines into sensitive or insensitive should I use -0.5 as a border or AM or 0 could also make sence to be used to count p-value?
It does not sound like you have much of an outgrowth at only +0.36. If you want a binary label of cells being negatively affected, I would use Gene Dependency scores, which are the probability that a given gene effect represents a true depleting effects. For a classifier, you can choose whatever probability threshold you want in gene dependency based on the balance you want between false positives and false negatives.
@DepMap_Staff
I’m an undergrad student, hoping you can help me. When I downloaded the dataset, CRISPR (Avana) Public 20Q4 how can I use R to compare the Gene Effect scores (CERES) of a certain mutation to all other cell lines because I downloaded the data and the spreadsheets first column is the name of cell lines in which are not the numeric scores. How can I compare the CERES scores using R?
