CRISPR common essentials seem to include both Achilles CRISPR data and Project SCORE data?
How about Achilles Common Essentials? Do it include both Achilles RNAi and Achilles CRISPR data?
It seems the most recent updates in 22Q1 only include CRISPR data, but not RNAi data? Is it still worth looking into previous RNAi data sets regarding gene dependency and effect? If yes, where can I find the most recent RNAi data set analyses?
I’m new to DepMap, and hope to get suggestions from folks here. Thanks!
No worries. I found that “custom download” helps find the most recent RNAi analyses.
Hi qzhang,
Glad you were able to find the data. RNAi has not been updated (other than very minor tweaks) since 2018. It does still have value that can’t be captured by CRISPRko, as you can see for example in Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal | bioRxiv. It also has risks, as you can see here: https://www.science.org/doi/10.1126/scitranslmed.aaw8412. These risks are mitigated in our data by combining many reagents and using DEMETER2, but it remains a noisier dataset than CRISPR.
As a general guideline:
- Genes that look more depleted in RNAi than CRISPR should be treated with caution, as they may well be due to uncorrected off-target effect.
- Genes that look less depleted in RNAi could reflect the difference between post-transcriptional suppression and genetic knockout.
In particular, genes that appear universally essential in CRISPR but variably essential in RNAi could, potentially, be interesting therapeutic targets. The hypothesis is that a small molecule inhibitor would be closer to the RNAi than the CRISPR phenotype and therefore also be selective. Note that this has not actually been demonstrated afaik.
Regarding CRISPR vs Achilles common essentials, Achilles common essentials are derived from Achilles gene effect and CRISPR common essentials are derived from CRISPR (the combined Achilles and Score) dataset.
Best,
Josh
Hi Josh,
If knocking out a gene promotes cell proliferation, how does it affect the CRISPR dependency score? Will it have a similar score to the genes that do not affect cell proliferation?
Best,
Q
Hi Qiao,
Yes, it will have a dependency score very close to 0. Gene effect is what should be used to identify knockouts that promote proliferation.
Best,
Josh
Thanks Josh! Is there any instruction about how to upload and view PRISM data in depmap? We got some files from a collaborator, and I would like to check the data in DepMap.
Is this the correct link?: https://depmap.org/portal/interactive/?x=slice%2FRNAi_merged%2F25783%2Fentity_id&y=slice%2Fexpression%2F20467%2Fentity_id
What should be entered for Units?
Hi qzhang, I’m afraid I don’t know anything about uploading PRISM data to the portal. @pmontgom any advice?
