A simple method to improve probe set estimates from oligonucleotide arrays.
A popular commercially available oligonucleotide microarray technology employs sets of 25 base pair oligonucleotide probes for measurement of gene expression levels. A mathematical algorithm is required to compute an estimate of gene expression from the multiple probes. Previously proposed methods for summarizing gene expression data have either been substantially ad hoc or have relied on model assumptions that may be easily violated. Here we present a new algorithm for calculating gene expression from probe sets. Our approach is functionally related to leave-one-out cross-validation, a non-parametric statistical technique that is often applied in limited data situations. We illustrate this approach using data from our study seeking a molecular fingerprint of STAT3 regulated genes for early detection of human cancer.
Lazaridis
Emmanuel N
EN
H. Lee Moffitt Cancer Center & Research Institute, University of South Florida, 12902 Magnolia Drive, MRC-CANCONT Tampa, FL 33612-9497, USA. lazarien@iarc.fr
Sinibaldi
Dominic
D
Bloom
Gregory
G
Mane
Shrikant
S
Jove
Richard
R
D000465:Algorithms; D004268:DNA-Binding Proteins / Q000235:genetics; D006801:Humans; D009369:Neoplasms / Q000175:diagnosis / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015345:Oligonucleotide Probes / Q000592:standards*; D050796:STAT3 Transcription Factor; D018709:Statistics, Nonparametric; D015534:Trans-Activators / Q000235:genetics
D004268:DNA-Binding Proteins; D015345:Oligonucleotide Probes; D050796:STAT3 Transcription Factor; C494086:STAT3 protein, human; D015534:Trans-Activators