Comparison of normalization methods for Illumina BeadChip HumanHT-12 v3.
BACKGROUND
Normalization of microarrays is a standard practice to account for and minimize effects which are not due to the controlled factors in an experiment. There is an overwhelming number of different methods that can be applied, none of which is ideally suited for all experimental designs. Thus, it is important to identify a normalization method appropriate for the experimental setup under consideration that is neither too negligent nor too stringent. Major aim is to derive optimal results from the underlying experiment. Comparisons of different normalization methods have already been conducted, none of which, to our knowledge, comparing more than a handful of methods.


RESULTS
In the present study, 25 different ways of pre-processing Illumina Sentrix BeadChip array data are compared. Among others, methods provided by the BeadStudio software are taken into account. Looking at different statistical measures, we point out the ideal versus the actual observations. Additionally, we compare qRT-PCR measurements of transcripts from different ranges of expression intensities to the respective normalized values of the microarray data. Taking together all different kinds of measures, the ideal method for our dataset is identified.


CONCLUSIONS
Pre-processing of microarray gene expression experiments has been shown to influence further downstream analysis to a great extent and thus has to be carefully chosen based on the design of the experiment. This study provides a recommendation for deciding which normalization method is best suited for a particular experimental setup.
Boehringer Ingelheim Pharma GmbH & Co, KG, Birkendorfer Str, 65, 88397 Biberach/Riss, Germany.
Ramona
R
Schmid
Patrick
P
Baum
Carina
C
Ittrich
Katrin
K
Fundel-Clemens
Wolfgang
W
Huber
Benedikt
B
Brors
Roland
R
Eils
Andreas
A
Weith
Detlev
D
Mennerich
Karsten
K
Quast
D000704:Analysis of Variance; D002460:Cell Line; D020869:Gene Expression Profiling; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*; D034741:RNA, Small Interfering / Q000235:genetics; D020133:Reverse Transcriptase Polymerase Chain Reaction; D019914:Taq Polymerase / Q000378:metabolism; D013997:Time Factors; D016212:Transforming Growth Factor beta / Q000494:pharmacology
D034741:RNA, Small Interfering; D016212:Transforming Growth Factor beta; D019914:Taq Polymerase