title: Nonparametric Tests for Differential Histone Enrichment with ChIP-Seq Data.
abstract: Chromatin immunoprecipitation sequencing (ChIP-seq) is a powerful method for analyzing protein interactions with DNA. It can be applied to identify the binding sites of transcription factors (TFs) and genomic landscape of histone modification marks (HMs). Previous research has largely focused on developing peak-calling procedures to detect the binding sites for TFs. However, these procedures may fail when applied to ChIP-seq data of HMs, which have diffuse signals and multiple local peaks. In addition, it is important to identify genes with differential histone enrichment regions between two experimental conditions, such as different cellular states or different time points. Parametric methods based on Poisson/negative binomial distribution have been proposed to address this differential enrichment problem and most of these methods require biological replications. However, many ChIP-seq data usually have a few or even no replicates. We propose a nonparametric method to identify the genes with differential histone enrichment regions even without replicates. Our method is based on nonparametric hypothesis testing and kernel smoothing in order to capture the spatial differences in histone-enriched profiles. We demonstrate the method using ChIP-seq data on a comparative epigenomic profiling of adipogenesis of murine adipose stromal cells and the Encyclopedia of DNA Elements (ENCODE) ChIP-seq data. Our method identifies many genes with differential H3K27ac histone enrichment profiles at gene promoter regions between proliferating preadipocytes and mature adipocytes in murine 3T3-L1 cells. The test statistics also correlate with the gene expression changes well and are predictive to gene expression changes, indicating that the identified differentially enriched regions are indeed biologically meaningful.
authors: Department of Biostatistics and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
authors: Qian
authors: Q
authors: Wu
authors: Department of Biostatistics and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
authors: Kyoung-Jae
authors: KJ
authors: Won
authors: Department of Biostatistics and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
authors: Hongzhe
authors: H
authors: Li
keywords: kernel smoothing; nonparametric testing; normalization; spatial histone profiles
references: Stat Methods Med Res. 1995 Sep;4(3):187-96
references: 8548102
references: J Am Stat Assoc. 2011;106(495):891-903
references: 26478641
references: Bioinformatics. 2009 Sep 15;25(18):2334-40
references: 19561022
references: Cell. 2007 May 18;129(4):823-37
references: 17512414
references: Genome Biol. 2008;9(9):R137
references: 18798982
references: Proc Natl Acad Sci U S A. 2001 Apr 24;98(9):5116-21
references: 11309499
references: PLoS Comput Biol. 2009 Nov;5(11):e1000566
references: 19918365
references: Science. 2007 Jun 8;316(5830):1497-502
references: 17540862
references: Methods Mol Biol. 2011;791:265-86
references: 21913086
references: Cell. 2010 Oct 1;143(1):156-69
references: 20887899
references: BMC Genomics. 2011 Nov 03;12:544
references: 22047616
references: Genome Biol. 2009;10(3):R25
references: 19261174
references: Nat Biotechnol. 2008 Nov;26(11):1293-300
references: 18978777
references: Nat Rev Genet. 2009 Oct;10(10):669-80
references: 19736561
references: Proc Natl Acad Sci U S A. 2010 Feb 16;107(7):2926-31
references: 20133639
references: Proc Natl Acad Sci U S A. 1931 Dec;17(12):684-8
references: 16577411
references: BMC Bioinformatics. 2009 Sep 21;10:299
references: 19772557
references: Genome Biol. 2012 Mar 16;13(3):R16
references: 22424423
references: Nature. 2012 Sep 6;489(7414):57-74
references: 22955616
references: Nat Genet. 2010 Apr;42(4):343-7
references: 20208536
references: Bioinformatics. 2009 Aug 1;25(15):1952-8
references: 19505939
references: Nat Methods. 2008 Jul;5(7):621-8
references: 18516045
references: Bioinformatics. 2012 Jan 1;28(1):121-2
references: 22057161
references: Ann Appl Stat. 2013;7(1):471-494
references: 25411587
references: Genome Biol. 2012 Jun 13;13(9):R53
references: 22950368
references: Nature. 2011 Jul 24;476(7358):105-8
references: 21785438