methylGSA: A Bioconductor Package and Shiny App for DNA Methylation Data Length Bias Adjustment in Gene Set Testing

Details

• Personal Author:
  Kuan P-F ; Ren X
• Description:
  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://bio conductor.org/packages/methylGSA and Shiny app is available at: http://www.ams.sunysb.edu/ %7epfkuan/softwares.html#methylGSA. [Description provided by NIOSH]
• Subjects:
  Genetics Occupational Health Safety Software
• Keywords:
  Computer Applications Computer Software Deoxyribonucleic Acids DNA DNA Microarrays Genes Genetic Testing Ribonucleic Acids RNA
• ISSN:
  1367-4803
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  New York ; OSHA Region 2
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• NIOSHTIC Number:
  nn:20054515
• Citation:
  Bioinformatics 2019 Jun; 35(11):1958-1959
• Contact Point Address:
  Pei Fen Kuan, Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA
• Email:
  peifen.kuan@stonybrook.edu
• Federal Fiscal Year:
  2019
• Performing Organization:
  State University of New York at Stony Brook
• Peer Reviewed:
  True
• Start Date:
  20170701
• Source Full Name:
  Bioinformatics
• End Date:
  20200630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:43a43e511a905efd604073fe0c76a08605b4a2bc663852dfd9eb0cb81f6c2bb6522bba65f53860647c35ef0057a0fb28d9b1df22d28f0908508c66de28a50158
• Download URL:
  https://stacks.cdc.gov/view/cdc/217054/cdc_217054_DS1.pdf
• File Type:
  [PDF - 143.58 KB ]