A comparison of normalization methods for high density oligonucleotide array data based on variance and bias | Zendy

Benjamin M. Bolstad | Zendy; Rafael A. Irizarry | Zendy; Magnus Åstrand | Zendy; Terence P. Speed | Zendy

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A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

Author(s) -

Benjamin M. Bolstad,

Rafael A. Irizarry,

Magnus Åstrand,

Terence P. Speed

Publication year - 2003

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/19.2.185

Subject(s) - bioconductor , normalization (sociology) , computer science , r package , data mining , software , algorithm , linear scale , statistics , pattern recognition (psychology) , mathematics , artificial intelligence , biochemistry , chemistry , geodesy , sociology , anthropology , gene , programming language , geography

When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization is a process for reducing this variation. It is common to see non-linear relations between arrays and the standard normalization provided by Affymetrix does not perform well in these situations.

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