I would like your suggestion for the bioinformatics approaches how to select biomarker genes in the cancer cell lines. We have IC50 data for a compounds screening to about 100 cell line, resulted in compound sensitive or resistant for the cell lines. We would like to have tool to select gene or marker correlated with the gene expression or copy number changes. How can we use the public data (e.g. CCLE???s gene expression etc.) to select the genes or biomarkers ??? which correlate with the IC50 screening for the cell line? Thank you. -- output of sessionInfo(): - -- Sent via the guest posting facility at bioconductor.org.

Hi, On Sun, Jan 26, 2014 at 9:01 PM, Ran [guest] <guest at="" bioconductor.org=""> wrote: > > I would like your suggestion for the bioinformatics approaches how to select biomarker genes in the cancer cell lines. We have IC50 data for a compounds screening to about 100 cell line, resulted in compound sensitive or resistant for the cell lines. We would like to have tool to select gene or marker correlated with the gene expression or copy number changes. How can we use the public data (e.g. CCLE???s gene expression etc.) to select the genes or biomarkers ??? which correlate with the IC50 screening for the cell line? Thank you. The most obvious thing to do is to just mimic what they reported to have done in their original publication: Systematic identification of genomic markers of drug sensitivity in cancer cells http://www.nature.com/nature/journal/v483/n7391/abs/nature11005.html They combined different types of "omics" measurements from the cell lines they have drug response data from and used them as features for their favorite machine learning algorithm (the elastic net (implented in the glmnet package on CRAN)) to predict drug response (measured in a few different ways). It's easy to say. Easy "enough" to do. Difficult to do correctly, but I will leave it at that. HTH, -steve -- Steve Lianoglou Computational Biologist Genentech