Multivariate segmentation in the analysis of transcription tiling array data.
Tiling DNA microarrays extend current microarray technology by probing the non-repeat portion of a genome at regular intervals in an unbiased fashion. A fundamental problem in the analysis of these data is the detection of genomic regions that are differentially transcribed across multiple conditions. We propose a linear time algorithm based on segmentation techniques and linear modeling that can work at a user-selected false discovery rate (FDR). It also attains a fourfold sensitivity gain over the only competing algorithm when applied to a whole genome transcription data set spanning the embryonic development of Drosophila melanogaster.
Piccolboni
Antonio
A
Affymetrix, Inc., Emeryville, California, USA. antonio_piccolboni@affymetrix.com
D000465:Algorithms; D000818:Animals; D030541:Databases, Genetic; D004331:Drosophila melanogaster / Q000196:embryology / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods*; D016678:Genome; D008957:Models, Genetic; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods; D014158:Transcription, Genetic