Cancer Data Science

Fighting cancer with machine learning @ Broad Institute

[Cancer Data Science @CancerDataSci]

While the focus in the clinical setting has been on finding DNA-based cancer biomarkers, in a study led by Josh Dempster we show that, at least in vitro, gene expression is generally a more powerful biomarker for cancer vulnerabilities https://t.co/uaZW3XuBTY @CancerDepMap

[The Cancer Dependency Map @CancerDepMap]

Congratulations to @corsellos on the Drug Repurposing paper published today @NatureCancer! An unexpectedly large number of non-oncology drugs selectively inhibit subsets of cancer cell lines: https://t.co/wrHgk8U9YC

[Cancer Data Science @CancerDataSci]

We've just released the MIX-seq manuscript, data and code. Congrats James, Brent, Allie, Katie and the rest of the team for this cool work!

[The Cancer Dependency Map @CancerDepMap]

Excited to share our preprint describing MIX-seq [https://t.co/e1WCvOlkrk]! MIX-seq is an approach for multiplexed transcriptional profiling of chemical and genetic perturbations in large pools of co-treated cancer cell lines, with single-cell resolution. (1/5)

[The Cancer Dependency Map @CancerDepMap]

REPURPOSING HUB DATA AND PREPRINT NOW OUT!! See how >4500 existing compounds performed when used across >550 cancer cell lines 💊 https://t.co/WK5d3UGRla, data can be found on the #DepMap portal: https://t.co/pbOgI5fT2D

[The Cancer Dependency Map @CancerDepMap]

19Q3 Cancer Dependency data now live!
#CRISPR knockout screening data for 64 (😲!) new #cancer cell lines, plus accompanying gene expression, copy number and mutation profiles: https://t.co/dQjWYpfsN8

[Cancer Data Science @CancerDataSci]

Are the CRISPR screens published by Sanger today consistent with those done at Broad? We teamed up with @DepMapSanger to find out. The results are in: https://t.co/cSWGOU39fD @CancerDepMap @biorxivpreprint #OpenScience

[The Cancer Dependency Map @CancerDepMap]

We’re excited to announce the release of a paper describing a new synthetic lethal target in MSI tumors as part of our GI Dependency Map! https://t.co/g40aglMD2u #Cancer #DepMap

[Cancer Data Science @CancerDataSci]

The largest dataset of cancer genetic dependencies to date includes RNAi data for 712 cell lines from Achilles, DRIVE and Marcotte et al., created using our new method DEMETER2, now out in Nat Comms. https://t.co/atJUNxCJ6M for data, code and paper @CancerDepMap @broadinstitute

[Cancer Data Science @CancerDataSci]

A great example of how @CancerDepMap genetic screens can be used to study protein complex function. https://t.co/Mzy8KRZi8r Congrats to @joshbiology and @_robin_meyers_!

[The Cancer Dependency Map @CancerDepMap]

18Q2 data release is here! https://t.co/dQjWYpfsN8

[Cancer Data Science @CancerDataSci]

The largest dataset of cancer genetic dependencies: More than 970 RNAi screens in 713 cell lines from @broadinstitute Achilles, Novartis DRIVE and Marcotte et al., 2016 processed together by the new DEMETER2 method. https://t.co/evgMthBhYh @CancerDepMap @biorxivpreprint

[The Cancer Dependency Map @CancerDepMap]

We have a new portal! https://t.co/5GCQyc9pSc Integrated genome-scale #CRISPR LoF, sm mol sensitivity & #RNAi knockdown screen data on 500+ #cancer cell lines together w/ user-friendly analysis & #dataviz tools

[Cancer Data Science @CancerDataSci]

Now available from @CancerDepMap: #CRISPRscreen data from 391 #cancer lines, incl 51 new lines (representing 14 tumor types): https://t.co/8W50mnB1Cj Accompanying #RNAseq + #WES profiles: https://t.co/ZjKjk8qff3. More to come on a quarterly basis!

[Cancer Data Science @CancerDataSci]

342 CRISPR KO screens in cancer cell lines and our method to correct for CRISPR/CN effect, now live https://t.co/opkCKmVPfX @broadinstitute

[Cancer Data Science @CancerDataSci]

Our first effort to define a Cancer Dependency Map is now live at https://t.co/ftZR67725n and https://t.co/72J5KxYNXC @broadinstitute

[Cancer Data Science @CancerDataSci]

@pedrobeltrao We're working to release all data and code soon!

[Cancer Data Science @CancerDataSci]

CERES corrects the copy-number effect of CRISPR-Cas9 essentiality screens in 342 cancer cell lines #bioRxiv https://t.co/EoEGRFwZQz