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BMC Genomics. 2016 Aug 12;17(1):632. doi: 10.1186/s12864-016-2963-0.

iTAR: a web server for identifying target genes of transcription factors using ChIP-seq or ChIP-chip data.

Yang CC1,2, Andrews EH3, Chen MH2,4, Wang WY2, Chen JJ1,4,5, Gerstein M6,7, Liu CC8,9,10, Cheng C11,12,13.

Author information

1
Institute of Molecular Biology, National Chung Hsing University, Taichung, 402, Taiwan.
2
Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung, 402, Taiwan.
3
Geisel School of Medicine at Dartmouth, Institute for Quantitative Biomedical Sciences, Lebanon, NH, 03766, USA.
4
Institute of Biomedical Sciences, National Chung Hsing University, Taichung, 402, Taiwan.
5
Agricultural Biotechnology Center, National Chung Hsing University, Taichung, 402, Taiwan.
6
Program in Computational Biology and Bioinformatics, Yale University, 260 Whitney Avenue, New Haven, CT, 06520, USA.
7
Department of Molecular Biophysics and Biochemistry, Yale University, 260 Whitney Avenue, New Haven, CT, 06520, USA.
8
Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung, 402, Taiwan. jimliu@nchu.edu.tw.
9
Institute of Biomedical Sciences, National Chung Hsing University, Taichung, 402, Taiwan. jimliu@nchu.edu.tw.
10
Agricultural Biotechnology Center, National Chung Hsing University, Taichung, 402, Taiwan. jimliu@nchu.edu.tw.
11
Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH, 03755, USA. chao.cheng@dartmouth.edu.
12
Geisel School of Medicine at Dartmouth, Institute for Quantitative Biomedical Sciences, Lebanon, NH, 03766, USA. chao.cheng@dartmouth.edu.
13
Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03766, USA. chao.cheng@dartmouth.edu.

Abstract

BACKGROUND:

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) or microarray hybridization (ChIP-chip) has been widely used to determine the genomic occupation of transcription factors (TFs). We have previously developed a probabilistic method, called TIP (Target Identification from Profiles), to identify TF target genes using ChIP-seq/ChIP-chip data. To achieve high specificity, TIP applies a conservative method to estimate significance of target genes, with the trade-off being a relatively low sensitivity of target gene identification compared to other methods. Additionally, TIP's output does not render binding-peak locations or intensity, information highly useful for visualization and general experimental biological use, while the variability of ChIP-seq/ChIP-chip file formats has made input into TIP more difficult than desired.

DESCRIPTION:

To improve upon these facets, here we present are fined TIP with key extensions. First, it implements a Gaussian mixture model for p-value estimation, increasing target gene identification sensitivity and more accurately capturing the shape of TF binding profile distributions. Second, it enables the incorporation of TF binding-peak data by identifying their locations in significant target gene promoter regions and quantifies their strengths. Finally, for full ease of implementation we have incorporated it into a web server ( http://syslab3.nchu.edu.tw/iTAR/ ) that enables flexibility of input file format, can be used across multiple species and genome assembly versions, and is freely available for public use. The web server additionally performs GO enrichment analysis for the identified target genes to reveal the potential function of the corresponding TF.

CONCLUSIONS:

The iTAR web server provides a user-friendly interface and supports target gene identification in seven species, ranging from yeast to human. To facilitate investigating the quality of ChIP-seq/ChIP-chip data, the web server generates the chart of the characteristic binding profiles and the density plot of normalized regulatory scores. The iTAR web server is a useful tool in identifying TF target genes from ChIP-seq/ChIP-chip data and discovering biological insights.

KEYWORDS:

ChIP-chip; ChIP-seq; Gaussian mixture model; Gene ontology analysis; Transcription factor

PMID:
27519564
PMCID:
PMC4983039
DOI:
10.1186/s12864-016-2963-0
[Indexed for MEDLINE]
Free PMC Article

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