Assessment of the relationship between pre-chip and post-chip quality measures for Affymetrix GeneChip expression data.

BMC Bioinformatics
Lesley JonesAngela K Hodges

Abstract

Gene expression microarray experiments are expensive to conduct and guidelines for acceptable quality control at intermediate steps before and after the samples are hybridised to chips are vague. We conducted an experiment hybridising RNA from human brain to 117 U133A Affymetrix GeneChips and used these data to explore the relationship between 4 pre-chip variables and 22 post-chip outcomes and quality control measures. We found that the pre-chip variables were significantly correlated with each other but that this correlation was strongest between measures of RNA quality and cRNA yield. Post-mortem interval was negatively correlated with these variables. Four principal components, reflecting array outliers, array adjustment, hybridisation noise and RNA integrity, explain about 75% of the total post-chip measure variability. Two significant canonical correlations existed between the pre-chip and post-chip variables, derived from MAS 5.0, dChip and the Bioconductor packages affy and affyPLM. The strongest (CANCOR 0.838, p < 0.0001) correlated RNA integrity and yield with post chip quality control (QC) measures indexing 3'/5' RNA ratios, bias or scaling of the chip and scaling of the variability of the signal across the chip. Post...Continue Reading

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Datasets Mentioned

BETA
GSE3790

Methods Mentioned

BETA
chip
chips

Software Mentioned

SAS
affy
dChip
GCOS
GeneChip
Agilent
affy package
affyPLM
Bioconductor affy package
RNADEG SL

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