Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization.
Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This "spike" chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes.
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland;
Nicolas
N
Bonhoure
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland;
Gergana
G
Bounova
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland;
David
D
Bernasconi
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland;
Viviane
V
Praz
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland;
Fabienne
F
Lammers
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland;
Donatella
D
Canella
Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York 10461, USA;
Ian M
IM
Willis
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland;
Winship
W
Herr
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland;
Nouria
N
Hernandez
Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Department of Oncology and the Ludwig Center for Cancer Research, Faculty of Biology and Medicine, University of Lausanne, 1011 Lausanne, Switzerland.
Mauro
M
Delorenzi
D000818:Animals; D002843:Chromatin / Q000235:genetics / Q000378:metabolism; D047369:Chromatin Immunoprecipitation / Q000379:methods* / Q000592:standards; D019295:Computational Biology / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods* / Q000592:standards; D006801:Humans; D051379:Mice; D011786:Quality Control; D012015:Reference Standards; D015203:Reproducibility of Results
D002843:Chromatin