Design and analysis of ChIP-seq experiments for DNA-binding proteins.
Recent progress in massively parallel sequencing platforms has enabled genome-wide characterization of DNA-associated proteins using the combination of chromatin immunoprecipitation and sequencing (ChIP-seq). Although a variety of methods exist for analysis of the established alternative ChIP microarray (ChIP-chip), few approaches have been described for processing ChIP-seq data. To fill this gap, we propose an analysis pipeline specifically designed to detect protein-binding positions with high accuracy. Using previously reported data sets for three transcription factors, we illustrate methods for improving tag alignment and correcting for background signals. We compare the sensitivity and spatial precision of three peak detection algorithms with published methods, demonstrating gains in spatial precision when an asymmetric distribution of tags on positive and negative strands is considered. We also analyze the relationship between the depth of sequencing and characteristics of the detected binding positions, and provide a method for estimating the sequencing depth necessary for a desired coverage of protein binding sites.
Kharchenko
Peter V
PV
Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St., Boston, Massachusetts 02115, USA.
Tolstorukov
Michael Y
MY
Park
Peter J
PJ
D000465:Algorithms; D001665:Binding Sites; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D004268:DNA-Binding Proteins / Q000737:chemistry / Q000378:metabolism*; D011485:Protein Binding; D012107:Research Design; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software; D014157:Transcription Factors / Q000737:chemistry / Q000378:metabolism
D004268:DNA-Binding Proteins; D014157:Transcription Factors