On Selecting the Best Pre-processing Method for Affymetrix Genechips

被引：0

作者：

Florido, J. P. ^{[1
]}

Pomares, H. ^{[1
]}

Rojas, I. ^{[1
]}

Calvo, J. C. ^{[1
]}

Urquiza, J. M. ^{[1
]}

Gonzalo Claros, M. ^{[2
]}

机构：

[1] Univ Granada, Dept Comp Architecture & Comp Technol, Granada, Spain

[2] Univ Malaga, Dept Mol Biol & Biochem, Malaga, Spain

来源：

BIO-INSPIRED SYSTEMS: COMPUTATIONAL AND AMBIENT INTELLIGENCE, PT 1 | 2009年 / 5517卷

关键词：

PROBE LEVEL DATA; MICROARRAY EXPERIMENTS; NORMALIZATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Affymetrix High Oligonucleotide expression arrays, also known as Affymetrix GeneChips, are widely used for the high-throughput assessment of gene expression of thousands of genes simultaneously. Although disputed by several authors, there are non-biological variations and systematic biases that Must be removed as much as possible before in absolute expression level for every gene is assessed. Several pre-processing methods are available in the literature and five common ones (RMA, GCRMA, MAS5, dChip and VSN) and two customized Loess methods are benchmarked in terms of data variability, similarity of data distributions and correlation coefficient among replicated slides in a variety of real examples. Besides, it will be checked how the variant and invariant genes can influence on preprocessing performance.

引用

页码：845 / +

页数：2

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