I am trying to look at perturbation of a gene for example AGPAT1 in breast cancer. I look at a cell line and get 10 top genes for RNAi and 10 top genes for CRISPER. Are these genes up or down regulated after knockdown or RNAI treatment. Please explain as I am new to DepMap. Thanks
Hello! The top 10 preferentially essential genes for RNAi/CRISPR listed on the cell line page are the genes whose knockdown/silencing causes more depletion in a given screen compared to the mean of all other screens. However this does not sound like what you are looking for.
If you are looking for the effect of AGPAT1 knockout on cell fitness for a set of breast cancer lines, you could use the data explorer tool to plot the distribution of CRISPR/RNAi gene effect scores for AGPAT1 in breast cancer lines. See example below:
If you are interested in the expression of AGPAT1 in these lines, again you could use the data explorer tool to either plot its distribution or to plot it against the gene effect score (by setting it as the y-axis). But please note this expression data is measured for the unperturbed cell line, not following CRISPR/RNAi screening.
Thank you. First I queried for AGPAT1. Then I looked at the perturbation effects. Selected a cell line and looked at the top genes in CRISPER and RNAi. I thought perturbation effect of the queried gene alteration is shown in this list. Looks like it is not. Does it mean that knock down/silencing of the top 10 preferential genes cause more depletion of the queried gene in that cell line. Am I correct.Thanks.
The top 10 preferentially essential genes on the cell line page are those with the lowest mean subtracted score when comparing to all other cell lines. Say gene X had a score of -2 in cell line Y but an average score of -0.5 across all other lines. Then X could be considered preferentially essential in Y. However, you could imagine a more depleted gene Z which scores -3 in cell line Y and -2 on average (ie. a common essential). So I would not assume that the top 10 genes listed for a cell line are necessarily the most depleted in that cell line.
If you are interested in AGPAT1’s score in relation to all other gene’s scores for a given cell line, I would suggest downloading the Achilles gene effect CSV and examining where AGPAT1 falls in the distribution of scores for your cell line of interest.