MACS

MACS calls peaks in chromatin immunoprecipitation sequencing (ChIP-seq) data from short-read sequencers such as Solexa's Genome Analyzer to locate protein–DNA binding sites.

Key Features:

• Empirical shift-size modeling: Models the shift size of ChIP-seq tags to improve the spatial resolution of predicted binding sites.
• Dynamic Poisson distribution: Uses a dynamic Poisson distribution to model local biases and adjust for variations in tag density across genomic regions.
• Comparative performance: Demonstrated superior performance relative to existing ChIP-seq peak-finding algorithms in comparative studies.

Scientific Applications:

• Protein–DNA interaction mapping: Identifies genomic regions bound by proteins to map protein–DNA interactions.
• Gene regulation and transcription factor networks: Locates transcription factor binding sites to inform studies of gene regulation and regulatory networks.
• Epigenetic modification studies: Provides binding-site localization useful for analyses of epigenetic modifications.

Methodology:

Empirical modeling of ChIP-seq tag shift size and application of a dynamic Poisson distribution to address local bias and variations in tag density.