Complete expression profile of gene knock-down

Hi everyone,
I was wondering if it is possible to download/extract the complete expression profile of a specific gene knock-down experiment for all available/processed cell-lines. So fare I was only able to find genearl expression profiles for cell-lines within the download section.
Thx a lot,
Bettina

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To make sure I understand what you’re asking, you would like to have gene expression profiles measured after a knock-down (RNAi? other method? no preference for method?) of some genes? So for example, RNA-seq of all CCLE cell lines after each cell line has had KD of gene X, then the same thing for gene Y etc.

Thx a lot for your reply and for the summary of my question. This is exactly what I’m looking for, dreaming of. I found the expression profiles for all the CCLE cell lines within the download section as well as the information about the perturbation effect in the CCLE cell lines [all or only dependent ones]. Hence, I was wondering if the expression profile of gene X [Xi -Xn] after a knock-down (no preference for the method) is also available for download.

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That would be amazing, to my knowledge that data is not available (someone from DepMap can correct me if I’m wrong though, would be very pleasantly surprised!)

The only thing I know of that is somewhat related is CMap / L1000 - they use a high-throughput gene expression assay to directly measure ~1000 genes, infer the expression of ~13,000. They’ve done that in ~8-12 cell lines with ~9000 perturbagens - KD of genes, overexpression of genes, treatment with tool compounds.
https://clue.io/

Hope this helps

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Too bad the data is not available, thx for confirming this. I thought maybe I just missed it. I appreciate your help and CMap recommendation. I’ll check it out.

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I think this is the goal of the next stage of the DepMap project, it looks like they’re applying for funding: https://www.nature.com/articles/d41586-021-00182-0

I hope they get it, the utility of something like this would be higher than other projects like ENCODE at a fraction of the cost, and would definitely extend beyond ‘cancer biology’

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@pathogen623 @bhalwachs Care to help us make the case for generating these data? :grinning:

What are the ways you envision yourselves and others using this type of data?

Which would be more useful for you to have first: data from genome-scale knockouts in only a few cell lines or from a limited number of KOs (~hundreds) in a set of ~100 cell lines?

PS: We have previously published post-perturbational transcriptional data (scRNA-seq) for up to 100 cell lines treated with a handful of drugs (as well as following GPX4 KO) as part of our MIX-seq study https://www.nature.com/articles/s41467-020-17440-w