Use model-based analysis of ChIP-Seq (MACS) to analyze short reads generated by sequencing protein–DNA interactions in embryonic stem cells
T Liu - Stem cell transcriptional networks: methods and …, 2014 - Springer
Stem cell transcriptional networks: methods and protocols, 2014•Springer
Abstract Model-based Analysis of ChIP-Seq (MACS) is a computational algorithm for
identifying genome-wide protein–DNA interaction from ChIP-Seq data. MACS combines
multiple modules to process aligned ChIP-Seq reads for either transcription factor or histone
modification by removing redundant reads, estimating fragment length, building signal
profile, calculating peak enrichment, and refining and reporting peak calls. In this protocol,
we provide a detailed demonstration of how to apply MACS to analyze ChIP-Seq datasets …
identifying genome-wide protein–DNA interaction from ChIP-Seq data. MACS combines
multiple modules to process aligned ChIP-Seq reads for either transcription factor or histone
modification by removing redundant reads, estimating fragment length, building signal
profile, calculating peak enrichment, and refining and reporting peak calls. In this protocol,
we provide a detailed demonstration of how to apply MACS to analyze ChIP-Seq datasets …
Abstract
Model-based Analysis of ChIP-Seq (MACS) is a computational algorithm for identifying genome-wide protein–DNA interaction from ChIP-Seq data. MACS combines multiple modules to process aligned ChIP-Seq reads for either transcription factor or histone modification by removing redundant reads, estimating fragment length, building signal profile, calculating peak enrichment, and refining and reporting peak calls. In this protocol, we provide a detailed demonstration of how to apply MACS to analyze ChIP-Seq datasets related to protein–DNA interactions in embryonic stem cells (ES cells). Instruction on how to interpret and visualize the results is also provided. MACS is an open-source and is available from http://github.com/taoliu/MACS .
Springer