Genomic analysis of early murine mammary gland development using novel probe-level algorithms.
We describe a novel algorithm (ChipStat) for detecting gene-expression changes utilizing probe-level comparisons of replicate Affymetrix oligonucleotide microarray data. A combined detection approach is shown to yield greater sensitivity than a number of widely used methodologies including SAM, dChip and logit-T. Using this approach, we identify alterations in functional pathways during murine neonatal-pubertal mammary development that include the coordinate upregulation of major urinary proteins and the downregulation of loci exhibiting reciprocal imprinting.
Master
Stephen R
SR
Department of Cancer Biology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104-6160, USA. srmaster@mail.med.upenn.edu
Stoddard
Alexander J
AJ
Bailey
L Charles
LC
Pan
Tien-Chi
TC
Dugan
Katherine D
KD
Chodosh
Lewis A
LA
D000465:Algorithms; D000818:Animals; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D023281:Genomics / Q000379:methods; D008321:Mammary Glands, Animal / Q000254:growth & development* / Q000378:metabolism*; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015345:Oligonucleotide Probes
D015345:Oligonucleotide Probes