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16 lines
945 B
Text
16 lines
945 B
Text
MACS: Model-based Analysis of ChIP-Seq
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Next generation parallel sequencing technologies made chromatin
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immunoprecipitation followed by sequencing (ChIP-Seq) a popular
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strategy to study genome-wide protein-DNA interactions, while creating
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challenges for analysis algorithms. We present Model-based Analysis of
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ChIP-Seq (MACS) on short reads sequencers such as Genome Analyzer
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(Illumina / Solexa). MACS empirically models the length of the
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sequenced ChIP fragments, which tends to be shorter than sonication or
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library construction size estimates, and uses it to improve the
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spatial resolution of predicted binding sites. MACS also uses a
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dynamic Poisson distribution to effectively capture local biases in
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the genome sequence, allowing for more sensitive and robust
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prediction. MACS compares favorably to existing ChIP-Seq peak-finding
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algorithms, is publicly available open source, and can be used for
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ChIP-Seq with or without control samples.
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