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

被引：103

作者：

Balwierz, Piotr J. ^{[1
,2
]}

Carninci, Piero ^{[3
]}

Daub, Carsten O. ^{[3
]}

Kawai, Jun ^{[3
]}

Hayashizaki, Yoshihide ^{[3
]}

Van Belle, Werner ^{[4
]}

Beisel, Christian ^{[4
]}

van Nimwegen, Erik ^{[1
,2
]}

机构：

[1] Univ Basel, Biozentrum, CH-4056 Basel, Switzerland

[2] Swiss Inst Bioinformat, CH-4056 Basel, Switzerland

[3] RIKEN Yokohama Inst, RIKEN Om Sci Ctr, Tsurumi Ku, Kanagawa 2300045, Japan

[4] Eidgenoss Tech Hsch Zurich, Dept Biosyst Sci & Engn, Lab Quantitat Genom, CH-4058 Basel, Switzerland

来源：

GENOME BIOLOGY | 2009年 / 10卷 / 07期

基金：

瑞士国家科学基金会;

关键词：

GENOME-WIDE ANALYSIS; GENE-EXPRESSION; TRANSCRIPTIONAL LANDSCAPE; CAP ANALYSIS; RNA-SEQ; REPRODUCIBILITY; ARRAYS; CAGE;

D O I：

10.1186/gb-2009-10-7-r79

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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.

引用

页数：21

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