Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

svaseq: removing batch effects and other unwanted noise from sequencing data

Jeffrey T. Leek
doi: https://doi.org/10.1101/006585
Jeffrey T. Leek
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: jtleek@gmail.com
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

It is now well known that unwanted noise and unmodeled artifacts such as batch effects can dramatically reduce the accuracy of statistical inference in genomic experiments. We introduced surrogate variable analysis for estimating these artifacts by (1) identifying the part of the genomic data only affected by artifacts and (2) estimating the artifacts with principal components or singular vectors of the subset of the data matrix. The resulting estimates of artifacts can be used in subsequent analyses as adjustment factors. Here I describe an update to the sva approach that can be applied to analyze count data or FPKMs from sequencing experiments. I also describe the addition of supervised sva (ssva) for using control probes to identify the part of the genomic data only affected by artifacts. These updates are available through the surrogate variable analysis (sva) Bioconductor package.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted June 25, 2014.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
svaseq: removing batch effects and other unwanted noise from sequencing data
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
svaseq: removing batch effects and other unwanted noise from sequencing data
Jeffrey T. Leek
bioRxiv 006585; doi: https://doi.org/10.1101/006585
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
svaseq: removing batch effects and other unwanted noise from sequencing data
Jeffrey T. Leek
bioRxiv 006585; doi: https://doi.org/10.1101/006585

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3506)
  • Biochemistry (7348)
  • Bioengineering (5324)
  • Bioinformatics (20266)
  • Biophysics (10020)
  • Cancer Biology (7744)
  • Cell Biology (11306)
  • Clinical Trials (138)
  • Developmental Biology (6437)
  • Ecology (9954)
  • Epidemiology (2065)
  • Evolutionary Biology (13325)
  • Genetics (9361)
  • Genomics (12587)
  • Immunology (7702)
  • Microbiology (19027)
  • Molecular Biology (7444)
  • Neuroscience (41049)
  • Paleontology (300)
  • Pathology (1230)
  • Pharmacology and Toxicology (2138)
  • Physiology (3161)
  • Plant Biology (6861)
  • Scientific Communication and Education (1273)
  • Synthetic Biology (1897)
  • Systems Biology (5313)
  • Zoology (1089)