Assessing the quality of hybridized RNA in Affymetrix GeneChips using linear regression.
The quality of data from microarray analysis is highly dependent on the quality of RNA. Because of the lability of RNA, steps involved in tissue sampling, RNA purification, and RNA storage are known to potentially lead to the degradation of RNAs; therefore, assessment of RNA quality and integrity is essential. Existing methods for estimating the quality of RNA hybridized to a GeneChip either suffer from subjectivity or are inefficient in performance. To overcome these drawbacks, we propose a linear regression method for assessing RNA quality for a hybridized Genechip. In particular, our approach used the probe intensities from the .cel files that the Affymetrix software associates with each microarray. The effectiveness and the improvements of the proposed method over the existing methods are illustrated by the application of the method to the previously published 19 human Affymetrix microarray data sets for which external verification of RNA quality is available.
Li
Meijuan
M
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455-0378, USA. meijuanl@biostat.umn.edu
Reilly
Cavan
C
D001709:Biotechnology; D002292:Carcinoma, Renal Cell / Q000235:genetics; D030561:Databases, Nucleic Acid; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000235:genetics; D016014:Linear Models; D015233:Models, Statistical; D009693:Nucleic Acid Hybridization; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000592:standards / Q000706:statistics & numerical data; D010051:Ovarian Neoplasms / Q000235:genetics; D011786:Quality Control; D012313:RNA / Q000235:genetics* / Q000302:isolation & purification* / Q000592:standards; D012334:RNA, Neoplasm / Q000235:genetics / Q000302:isolation & purification
D012334:RNA, Neoplasm; D012313:RNA