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.

Design and analysis of ChIP-seq experiments for DNA-binding proteins.

SPP is a tool to analyze ChIP-seq data, developed to detect protein-binding positions. The algorithm includes a method for setting an estimated minimum sequencing coverage of protein binding sites.

SPP

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