The RAS Informatics Group creates software tools to organize and interpret data produced by the RAS Initiative. We also import “big data” from external projects and analyze it with a focus on the genes in the RAS pathway. By integrating internal and external data, we help improve understanding of RAS-driven cancers.
The RAS Initiative, together with groups from the University of California, San Francisco and the Broad Institute in Boston, have probed dozens of cancer cell lines for the effect of knocking down entire signaling nodes (such as all three RAS genes, all three RAF genes, etc.). Our group has played a major role in analyzing and interpreting the data (publication submitted) from this project, called siren.
Our group has also analyzed the “big data” produced by The Cancer Genome Atlas in the context of mutant or wild-type RAS genes (publication submitted).
We have built an architecture that stores, organizes, searches, and retrieves the data produced within the RAS Initiative.
- Analysis of RAS and RAS pathway gene expression in tumor and normal samples in The Cancer Genome Atlas data
- Analysis of siREN data (using pools of siRNAs to knock down signaling nodes in cancer cell lines) and integrating it with drug sensitivity data from the Genomics of Drug Sensitivity in Cancer study
- Development of on-line tools to store, track, and retrieve data from FNLCR RAS Initiative projects
Tools We Use
- Programming, web, and scripting languages
- Public genomics data sets such as IGCG and TCGA
- Databases including Oracle, mysql, and Filemaker
- Cell line datasets such as nci60, CCLE, COSMIC, and GDSC
- Data portals such as Biomart, cBIOportal, and caHUB
For more information, contact the RAS Informatics Group team lead:
Dr. Ming Yi