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Genome Biol. 2009;10(7):R79. doi: 10.1186/gb-2009-10-7-r79. Epub 2009 Jul 22.

Methods for analyzing deep sequencing expression data: constructing the human and mouse promoterome with deepCAGE data.

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1
Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, Klingelbergstrasse 50/70, 4056-CH, Basel, Switzerland.

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.

PMID:
19624849
PMCID:
PMC2728533
DOI:
10.1186/gb-2009-10-7-r79
[Indexed for MEDLINE]
Free PMC Article
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