Abstract
Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) offers a powerful means to study transcription factor binding on a genome-wide scale. While a number of advanced software packages have already become available for identifying ChIP-seq-binding sites, it has become evident that the choice of the package together with its adjustable parameters can considerably affect the biological conclusions made from the data. Therefore, to aid these choices, we have recently introduced a reproducibility-optimization procedure, which computationally adjusts the parameters of the popular peak detection algorithms for each ChIP-seq data separately. Here, we provide a detailed description of the procedure together with practical guidelines on how to apply its implementation, the peakROTS R-package, in a given ChIP-seq experiment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Park PJ (2009) ChIP-seq: advantages and challenges of a maturing technology. Nat Rev Genet 10:669–680
Elo LL, Järvenpää H, Tuomela S et al (2010) Genome-wide profiling of interleukin-4 and STAT6 transcription factor regulation of human Th2 cell programming. Immunity 32:852–862
Schmidt D, Wilson MD, Ballester B et al (2010) Variation in transcription factor binding among humans. Science 328:1036–1040
Northrup DL, Zhao K (2011) Application of ChIP-Seq and related techniques to the study of immune function. Immunity 34:830–842
Rozowsky J, Euskirchen G, Auerbach RK et al (2009) PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls. Nat Biotechnol 27:66–75
Farnham PJ (2009) Insights from genomic profiling of transcription factors. Nat Rev Genet 10:605–616
Pepke S, Wold B, Mortazavi A (2009) Computation for ChIP-seq and RNA-seq studies. Nat Methods 6:S22–S32
Zhang Y, Liu T, Meyer CA et al (2008) Model-based analysis of ChIP-Seq (MACS). Genome Biol 9:R137
Fejes AP, Robertson G, Bilenky M et al (2008) FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology. Bioinformatics 24:1729–1730
Valouev A, Johnson DS, Sundquist A et al (2008) Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data. Nat Methods 5:829–834
Muiño JM, Kaufmann K, van Ham RC et al (2011) ChIP-seq analysis in R (CSAR): an R package for the statistical detection of protein-bound genomic regions. Plant Methods 7:11
Laajala TD, Raghav S, Tuomela S et al (2009) A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments. BMC Genomics 10:618
Wilbanks EG, Facciotti MT (2010) Evaluation of algorithm performance in ChIP-seq peak detection. PLoS One 5:e11471
Szalkowski AM, Schmid CD (2011) Rapid innovation in ChIP-seq peak-calling algorithms is outdistancing benchmarking efforts. Brief Bioinform 2:626–633
Micsinai M, Parisi F, Strino F et al (2012) Picking ChIP-seq peak detectors for analyzing chromatin modification experiments. Nucleic Acids Res 40:e70
Elo LL, Kallio A, Laajala TD et al (2012) Optimized detection of transcription factor-binding sites in ChIP-seq experiments. Nucleic Acids Res 40:e1
Elo LL, Filén S, Lahesmaa R et al (2008) Reproducibility-optimized test statistic for ranking genes in microarray studies. IEEE/ACM Trans Comput Biol Bioinform 5:423–431
Elo LL, Hiissa J, Tuimala J et al (2009) Optimized detection of differential expression in global profiling experiments: case studies in clinical transcriptomic and quantitative proteomic datasets. Brief Bioinform 10:547–555
Cotney J, Leng J, Oh S et al (2012) Chromatin state signatures associated with tissue-specific gene expression and enhancer activity in the embryonic limb. Genome Res 22:1069–1080
Holmes KA, Hurtado A, Brown GD et al (2012) Transducin-like enhancer protein 1 mediates estrogen receptor binding and transcriptional activity in breast cancer cells. Proc Natl Acad Sci USA 109:2748–2753
Home P, Saha B, Ray S et al (2012) Altered subcellular localization of transcription factor TEAD4 regulates first mammalian cell lineage commitment. Proc Natl Acad Sci USA 109:7362–7367
Jishage M, Malik S, Wagner U et al (2012) Transcriptional regulation by Pol II(G) involving mediator and competitive interactions of Gdown1 and TFIIF with Pol II. Mol Cell 45:51–63
Meier K, Mathieu EL, Finkernagel F et al (2012) LINT, a novel dL(3)mbt-containing complex, represses malignant brain tumour signature genes. PLoS Genet 8:e1002676
Kallio MA, Tuimala JT, Hupponen T et al (2011) Chipster: user-friendly analysis software for microarray and other high-throughput data. BMC Genomics 12:507
Euskirchen GM, Rozowsky JS, Wei CL et al (2007) Mapping of transcription factor binding regions in mammalian cells by ChIP: comparison of array- and sequencing-based technologies. Genome Res 17:898–909
Johnson DS, Mortazavi A, Myers RM et al (2007) Genome-wide mapping of in vivo protein-DNA interactions. Science 316:1497–1502
Acknowledgments
The work was supported by the Academy of Finland (grants 127575, 218591).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this protocol
Cite this protocol
Kallio, A., Elo, L.L. (2013). Optimizing Detection of Transcription Factor-Binding Sites in ChIP-seq Experiments. In: Shomron, N. (eds) Deep Sequencing Data Analysis. Methods in Molecular Biology, vol 1038. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-514-9_11
Download citation
DOI: https://doi.org/10.1007/978-1-62703-514-9_11
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-62703-513-2
Online ISBN: 978-1-62703-514-9
eBook Packages: Springer Protocols