methylGSA：一个 Bioconductor 包和 Shiny 应用程序，用于在基因集测试中调整 DNA 甲基化数据长度偏差。

methylGSA: a Bioconductor package and Shiny app for DNA methylation data length bias adjustment in gene set testing.

机构信息

Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.

出版信息

Bioinformatics. 2019 Jun 1;35(11):1958-1959. doi: 10.1093/bioinformatics/bty892.

DOI:10.1093/bioinformatics/bty892

PMID:30346483

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.

摘要

动机

RNA 测序（RNA-Seq）或 DNA 甲基化分析后进行差异表达的一个重要下游分析是基因集测试，即将显著基因或 CpG 与已知的生物学特性相关联。然而，由于基因长度的差异，传统的基因集测试方法会导致偏置的 P 值。现有的考虑长度偏差的方法主要是为 RNA-Seq 数据开发的。对于使用 Illumina 阵列进行 DNA 甲基化数据的分析，需要单独的方法来调整 CpG 的数量，而不是基因长度。