Beadarray expression analysis using bioconductor

Matthew E. Ritchie; Mark J. Dunning; Mike L. Smith; Wei Shi; Andy G. Lynch

doi:10.1371/journal.pcbi.1002276

Beadarray expression analysis using bioconductor

Matthew E. Ritchie, Mark J. Dunning, Mike L. Smith, Wei Shi, Andy G. Lynch

Research output: Contribution to journal › Article › peer-review

Abstract

Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered.

Original language	English
Article number	e1002276
Journal	PLoS Computational Biology
Volume	7
Issue number	12
DOIs	https://doi.org/10.1371/journal.pcbi.1002276
Publication status	Published - Dec 2011

Access to Document

10.1371/journal.pcbi.1002276

Cite this

@article{5d24cb60587749b189b43bf265828732,

title = "Beadarray expression analysis using bioconductor",

abstract = "Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered.",

author = "Ritchie, {Matthew E.} and Dunning, {Mark J.} and Smith, {Mike L.} and Wei Shi and Lynch, {Andy G.}",

year = "2011",

month = dec,

doi = "10.1371/journal.pcbi.1002276",

language = "English",

volume = "7",

journal = "PLoS Computational Biology",

issn = "1553-734X",

publisher = "Public Library of Science",

number = "12",

}

TY - JOUR

T1 - Beadarray expression analysis using bioconductor

AU - Ritchie, Matthew E.

AU - Dunning, Mark J.

AU - Smith, Mike L.

AU - Shi, Wei

AU - Lynch, Andy G.

PY - 2011/12

Y1 - 2011/12

N2 - Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered.

AB - Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered.

UR - http://www.scopus.com/inward/record.url?scp=84855290008&partnerID=8YFLogxK

U2 - 10.1371/journal.pcbi.1002276

DO - 10.1371/journal.pcbi.1002276

M3 - Article

AN - SCOPUS:84855290008

SN - 1553-734X

VL - 7

JO - PLoS Computational Biology

JF - PLoS Computational Biology

IS - 12

M1 - e1002276

ER -

Beadarray expression analysis using bioconductor

Abstract

Access to Document

Other files and links

Fingerprint

Cite this