Xu Ren1, Pei Fen Kuan1. 1. Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
Abstract
MOTIVATION: An important downstream analysis following differential expression from RNA sequencing (RNA-Seq) or DNA methylation analysis is the gene set testing to relate significant genes or CpGs to known biological properties. However, the traditional gene set testing approaches result in biased P-values due to the difference in gene length. Existing methods accounting for length bias were primarily developed for RNA-Seq data. For DNA methylation data profiled using the Illumina arrays, separate methods adjusting for the number of CpGs instead of gene length are necessary. RESULTS: We developed methylGSA, a Bioconductor package for gene set testing in DNA methylation data. Our accompanying Shiny app provides an interactive way of accessing functions and visualizing the results in methylGSA package. AVAILABILITY AND IMPLEMENTATION: methylGSA is available at Bioconductor repository: https://bioconductor.org/packages/methylGSA and Shiny app is available at: http://www.ams.sunysb.edu/%7epfkuan/softwares.html#methylGSA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: An important downstream analysis following differential expression from RNA sequencing (RNA-Seq) or DNA methylation analysis is the gene set testing to relate significant genes or CpGs to known biological properties. However, the traditional gene set testing approaches result in biased P-values due to the difference in gene length. Existing methods accounting for length bias were primarily developed for RNA-Seq data. For DNA methylation data profiled using the Illumina arrays, separate methods adjusting for the number of CpGs instead of gene length are necessary. RESULTS: We developed methylGSA, a Bioconductor package for gene set testing in DNA methylation data. Our accompanying Shiny app provides an interactive way of accessing functions and visualizing the results in methylGSA package. AVAILABILITY AND IMPLEMENTATION: methylGSA is available at Bioconductor repository: https://bioconductor.org/packages/methylGSA and Shiny app is available at: http://www.ams.sunysb.edu/%7epfkuan/softwares.html#methylGSA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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