Differential analysis for high density tiling microarray data

• Published in: BMC bioinformatics Vol. 8; no. 1; p. 359
• Main Authors: Ghosh, Srinka, Hirsch, Heather A, Sekinger, Edward A, Kapranov, Philipp, Struhl, Kevin, Gingeras, Thomas R
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 24.09.2007; BioMed Central; BMC
• Subjects: Algorithms; Chromosome Mapping - methods; Computational Biology - methods; Decision Theory; DNA microarrays; DNA Probes - chemistry; Gene Components - genetics; Gene expression; Gene Expression Profiling - methods; Genomics; Genomics - methods; HL-60 Cells - drug effects; HL-60 Cells - physiology; Humans; Methodology; Models, Genetic; Oligonucleotide Array Sequence Analysis - methods; Predictive Value of Tests; Regulatory Sequences, Nucleic Acid - genetics; Transcription, Genetic - physiology; Tretinoin - administration & dosage; United States
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/1471-2105-8-359

High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. We have proposed a novel approach, based on a piece-wise function - to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10-13. The prototype R code has been made available as supplementary material [see Additional file 1].