Methods for analyzing deep sequencing expression data: constructing the human and mouse promoterome with deepCAGE data
- PMID: 19624849
- PMCID: PMC2728533
- DOI: 10.1186/gb-2009-10-7-r79
Methods for analyzing deep sequencing expression data: constructing the human and mouse promoterome with deepCAGE data
Abstract
With the advent of ultra high-throughput sequencing technologies, increasingly researchers are turning to deep sequencing for gene expression studies. Here we present a set of rigorous methods for normalization, quantification of noise, and co-expression analysis of deep sequencing data. Using these methods on 122 cap analysis of gene expression (CAGE) samples of transcription start sites, we construct genome-wide 'promoteromes' in human and mouse consisting of a three-tiered hierarchy of transcription start sites, transcription start clusters, and transcription start regions.
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- Maeda N, Nishiyori H, Nakamura M, Kawazu C, Murata M, Sano H, Hayashida K, Fukuda S, Tagami M, Hasegawa A, Murakami K, Schroder K, Hume KID, Hayashizaki Y, Carninci P, Suzuki H. Development of a DNA barcode tagging method for monitoring dynamic changes in gene expression by using an ultra high-throughput sequencer. Biotechniques. 2008;45:95–97. doi: 10.2144/000112814. - DOI - PubMed
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