Open pipelines for integrated tumor genome profiles reveal differences between pancreatic cancer tumors and cell lines
Year: 2015
Type: article
Abstract: We describe open, reproducible pipelines that create an integrated genomic profile of a cancer and use the profile to find mutations associated with disease and potentially useful drugs. These pipelines analyze high-throughput cancer exome and transcriptome sequence data together with public databases to find relevant mutations and drugs. The three pipelines that we have developed are: (1) an exome analysis pipeline, which uses whole or targeted tumor exome sequence data to produce a list of putative variants (no matched normal data are needed); (2) a transcriptome analysis pipeline that processes whole tumor transcriptome sequence (RNA-seq) data to compute gene expression and find potential gene fusions; and (3) an integrated variant analysis pipeline that uses the tumor variants from the exome pipeline and tumor gene expression from the transcriptome pipeline to identify deleterious and druggable mutations in all genes and in highly expressed genes. These pipelines are integrated into the popular Web platform Galaxy at http://usegalaxy.org/cancer to make them accessible and reproducible, thereby providing an approach for doing standardized, distributed analyses in clinical studies. We have used our pipeline to identify similarities and differences between pancreatic adenocarcinoma cancer cell lines and primary tumors.
Source: Cancer Medicine
DOI: 10.1002/cam4.360
Authors: Jeremy Goecks, Bassel F. El‐Rayes, Shishir K. Maithel, H. Jean Khoury, James Taylor, Michael R. Rossi
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $4,700
Awards: Dynamically scalable accessible analysis for next generation sequence data, Democratization of Data Analysis in Life Sciences Through Galaxy, A Turnkey Solution for Next Generation Sequence Data Analysis, G83632010, G9000071022, Winship Cancer Institute Cancer Center Support Grant, Democratization of Data Analysis in Life Sciences Through Galaxy
OpenAlex ID: W2035992963
