Introduction to CellMiner and rcellminer

January 18, 2016
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(This article was first published on r – Lunean, and kindly contributed to R-bloggers)

The NCI-60 cancer cell line panel has been used over the course of several decades as an anti-cancer drug screen. This panel was developed as part of the Developmental Therapeutics Program (DTP) of the U.S. National Cancer Institute (NCI). Thousands of compounds have been tested on the NCI-60, which have been extensively characterized by many platforms for gene and protein expression, copy number, mutation, and others. The purpose of the CellMiner project has been to integrate data from multiple platforms used to analyze the NCI-60 and to provide a powerful suite of tools for exploration of NCI-60 data.

The CellMiner project makes much of its work transparent in the community by providing data downloads for the datasets used by the project. The rcellminer R package adds to this effort by providing additional functionality to help R users access the CellMiner data, including both NCI-60 molecular profiling and drug response data. The package allows programmatic access to CellMiner’s gene and protein expression, copy number, whole exome mutations, as well as activity data for ∼21K compounds, with information on their structure, mechanism of action and repeat screens. In addition to the provided data, R functions simplify the visualization of compound structures, drug compound activity patterns and molecular feature profile. Lastly, several web applications have been embedded into the rcellminer R package that allow interactive data exploration.

The presentation below gives a brief overview of both the CellMiner and rcellminer. One introductory topic covered in the presentation how users can use rcellminer to run a “pattern comparison” analysis to quickly identify genes that by gene expression, copy number alterations, etc. and/or compounds screened on the NCI-60 that significantly correlate with a user-defined pattern of interest over the NCI-60 (e.g. the presence of drug activity only in renal cell lines). The presentation also provides links to additional rcellminer tutorial material.

Luna A, Rajapakse VN, Sousa FG, Gao J, Schultz N, Varma S, Reinhold W, Sander C, & Pommier Y (2015). rcellminer: exploring molecular profiles and drug response of the NCI-60 cell lines in R. Bioinformatics (Oxford, England) PMID: 26635141

            

The post Introduction to CellMiner and rcellminer appeared first on Lunean.

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