Dataset Information

Differential analysis for high density tiling microarray data.

ABSTRACT:

Background

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.

Results

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.

Conclusion

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].

SUBMITTER: Ghosh S

PROVIDER: S-EPMC2231405 | biostudies-literature | 2007 Sep

REPOSITORIES: biostudies-literature

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Publications

Differential analysis for high density tiling microarray data.

Ghosh Srinka S Hirsch Heather A HA Sekinger Edward A EA Kapranov Philipp P Struhl Kevin K Gingeras Thomas R TR

BMC bioinformatics 20070924

<h4>Background</h4>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 ...[more]

PMID: 17892592

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Project description:BackgroundDNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. Expression microarrays (EMA) contain probes for annotated open reading frames (ORF) and are widely used for the analysis of differential gene expression. By contrast, tiling microarrays (TMA) have a much higher probe density and provide unbiased genome-wide coverage. The purpose of this study was to develop a protocol to exploit the high resolution of TMAs for quantitative measurement of DNA strand-specific differential expression of annotated and non-annotated transcripts.ResultsWe extensively filtered probes present in Affymetrix Genechip Yeast Genome 2.0 expression and GeneChip S. pombe 1.0FR tiling microarrays to generate custom Chip Description Files (CDF) in order to compare their efficiency. We experimentally tested the potential of our approach by measuring the differential expression of 4904 genes in the yeast Schizosaccharomyces pombe growing under conditions of oxidative stress. The results showed a Pearson correlation coefficient of 0.943 between both platforms, indicating that TMAs are as reliable as EMAs for quantitative expression analysis. A significant advantage of TMAs over EMAs is the possibility of detecting non-annotated transcripts generated only under specific physiological conditions. To take full advantage of this property, we have used a target-labelling protocol that preserves the original polarity of the transcripts and, therefore, allows the strand-specific differential expression of non-annotated transcripts to be determined. By using a segmentation algorithm prior to generating the corresponding custom CDFs, we identified and quantitatively measured the expression of 510 transcripts longer than 180 nucleotides and not overlapping previously annotated ORFs that were differentially expressed at least 2-fold under oxidative stress.ConclusionsWe show that the information derived from TMA hybridization can be processed simultaneously for high-resolution qualitative and quantitative analysis of the differential expression of well-characterized genes and of previously non-annotated and antisense transcripts. The consistency of the performance of TMA, their genome-wide coverage and adaptability to updated genome annotations, and the possibility of measuring strand-specific differential expression makes them a tool of choice for the analysis of gene expression in any organism for which TMA platforms are available.

Dataset Information

Differential analysis for high density tiling microarray data.

Background

Results

Conclusion

Publications

Differential analysis for high density tiling microarray data.

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