BeadArray Expression Analysis Using Bioconductor | Zendy

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

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BeadArray Expression Analysis Using Bioconductor

Author(s) -

Matthew E. Ritchie,

Mark Dunning,

Mike L. Smith,

Wei Shi,

Andy G. Lynch

Publication year - 2011

Publication title -

plos computational biology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.628

H-Index - 182

eISSN - 1553-7358

pISSN - 1553-734X

DOI - 10.1371/journal.pcbi.1002276

Subject(s) - bioconductor , computer science , preprocessor , software , data mining , annotation , exploit , gene expression profiling , data science , information retrieval , computational biology , artificial intelligence , biology , gene expression , genetics , gene , computer security , programming language

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.

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