Universität zu Köln

Stricker, Georg ORCID: 0000-0003-2949-1758, Engelhardt, Alexander, Schulz, Daniel, Schmid, Matthias ORCID: 0000-0002-0788-0317, Tresch, Achim and Gagneur, Julien ORCID: 0000-0002-8924-8365 (2017). GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis. Bioinformatics, 33 (15). S. 2258 - 2266. OXFORD: OXFORD UNIV PRESS. ISSN 1460-2059

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Abstract

Motivation: Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used approach to study protein-DNA interactions. Often, the quantities of interest are the differential occupancies relative to controls, between genetic backgrounds, treatments, or combinations thereof. Current methods for differential occupancy of ChIP-Seq data rely however on binning or sliding window techniques, for which the choice of the window and bin sizes are subjective. Results: Here, we present GenoGAM (Genome-wide Generalized Additive Model), which brings the well-established and flexible generalized additive models framework to genomic applications using a data parallelism strategy. We model ChIP-Seq read count frequencies as products of smooth functions along chromosomes. Smoothing parameters are objectively estimated from the data by cross-validation, eliminating ad hoc binning and windowing needed by current approaches. GenoGAM provides base-level and region-level significance testing for full factorial designs. Application to a ChIP-Seq dataset in yeast showed increased sensitivity over existing differential occupancy methods while controlling for type I error rate. By analyzing a set of DNA methylation data and illustrating an extension to a peak caller, we further demonstrate the potential of GenoGAM as a generic statistical modeling tool for genome-wide assays.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Stricker, Georg UNSPECIFIED orcid.org/0000-0003-2949-1758 UNSPECIFIED Engelhardt, Alexander UNSPECIFIED UNSPECIFIED UNSPECIFIED Schulz, Daniel UNSPECIFIED UNSPECIFIED UNSPECIFIED Schmid, Matthias UNSPECIFIED orcid.org/0000-0002-0788-0317 UNSPECIFIED Tresch, Achim UNSPECIFIED UNSPECIFIED UNSPECIFIED Gagneur, Julien UNSPECIFIED orcid.org/0000-0002-8924-8365 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-223479
DOI:	10.1093/bioinformatics/btx150
Journal or Publication Title:	Bioinformatics
Volume:	33
Number:	15
Page Range:	S. 2258 - 2266
Date:	2017
Publisher:	OXFORD UNIV PRESS
Place of Publication:	OXFORD
ISSN:	1460-2059
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language ASSOCIATION; REGIONS; PEAKS Multiple languages Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/22347