MACS2 v2.1.1.20160309

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

Accessing the software

To load the module:

$ module load MACS2/2.1.1.20160309-iomkl-2018a-Python-2.7.14

An example command to include in your job script:

macs2 callpeak -t <treatment-file> -c <control-file>

Accessing Previous Versions

Wherever possible, previous versions of this application will be retained for continuity, especially for research projects that require a consistent version of the software throughout the project. Such versions, however, may be unsupported by IT Services or the applications vendor, and may be withdrawn at short or no notice if they can no longer run on the cluster - for example, essential operating system upgrades may be incompatible with old versions.

The following previous versions of this application are available:

Known Problems & Limitations

None.

Other Information

The Support Level for this application is An.

Visit the MACS2 Python Package page for more information regarding this application.


Last modified: 5 March 2018