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    Genome Biol. 2009;10(7):R79. Epub 2009 Jul 22.

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

    Balwierz PJ, Carninci P, Daub CO, Kawai J, Hayashizaki Y, Van Belle W, Beisel C, van Nimwegen E.

    Source

    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
    [PubMed - indexed for MEDLINE]
    PMCID:
    PMC2728533
    Free PMC Article

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