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Genomatix: MACS - Model based Analysis for ChIPSeq
(only available on GGA)


[Introduction] [Parameters] [Output]

Introduction

One algorithm for peak calling is the MACS algorithm (Model based Analysis for ChIPSeq), that analyzes tags from ChIP-Seq data sets and finds significant regions for further analysis with other Genomatix tasks.

It thus represents a clustering algorithm for ChIPSeq data like NGSAnalyzer or SICER.
Genomatix integrated two versions of MACS: MACS (version 1.4) and MACS2 (version 2.1), which will give different results.

Details of the original MACS algorithm are described in

Zhang et al.: Model-based Analysis of ChIP-Seq (MACS).
Genome Biol (2008) vol. 9 (9) pp. R137

For details of the latest version of MACS2 you can see this python site. There is no paper available yet for MACS2, please cite the MACS paper above.

This Genomatix task automatically sets a number of parameters for MACS (e.g. genome size), thus simplifying the usage. The output comprises the original MACS output, as well as the visualisation of the peak model. Resulting clusters can be downloaded as BED files or directly saved to the project managment to be used with other tasks.


Parameters

MACS/MACS2 parameters
Narrow/broad peaks
(only for MACS2)
When the broad peak flag is on, MACS2 will try to composite broad regions by putting nearby highly enriched regions into a broad region with loose cutoff.
When broad peaks are called, the no-model option is automatically set (i.e. this overrides the mfold parameters below).
Suggested for some histone modifications, not for ChIPSeq.
Tag size The length of the input tags/reads. This value can be determined from the input file, by reading the first 100 regions and calculating the average region length.
q-value
(only for MACS2)
The q-value (minimum FDR) cutoff to call significant regions. Default is 0.01.
For broad marks, you can try 0.05 as cutoff.
Q-values are calculated from p-values using Benjamini-Hochberg procedure.
p-value
(only for MACS1.4)
P-value cutoff for peak detection. Default is 1e-5
Bandwidth This value is used while building the shifting model. Default is: 300
model fold (mfold) parameter The upper and lower model fold values for MACS to select the regions with a high-confidence enrichment ratio against background to build a model. If no models are found, the no-model option is used by MACS automatically.
Redundancy threshold The number of copies of identical reads allowed in a library. Values can be 'auto', 'all' or an integer
  • 'auto': MACS calculates the maximum tags at the exact same location based on binomial distribution using 1e-5 as p-value cutoff
  • 'all': all input tags are kept
  • integer: at most this number of tags will be kept at the same location

Output ('Complete Clustering Results')

Analysis Parameters

Here, the analysis parameters like input files, result name, database version (i.e. underlying genome), the MACS/MACS2 version and the parameters are shown.

Cluster detection

A summary with cluster statistics is displayed, including number of clusters found, number of reads within clusters and avergae cluster length.

MACS/MACS2 Output

The original MACS/MACS2 output is listed.

Peak Model

The peak model graphics is displayed (here as a PNG graphic), which is generated by MACS when calling the resulting R script.
With MACS2 additionally a cross-correlation graph is depicted.

Direct download of result files for further analysis with other tasks

The resulting BED file containing the clusters/peaks can be downloaded or can directly be saved into the project management for further analysis with other tasks. The BED file includes the PHRED like quality score (see below) for each region.

An Excel™ file called "macs_peaks.xls" with details produced by MACS/MACS2 can also be downloaded here. It contains information about called peaks. You can open it in Excel™ and sort/filter using excel functions.
For MACS, the information includes:

For MACS2, the information includes:

Note that the BED file format is zero-based and half-open, whereas numbering in the tab-separated Excel™ file is based at 1 and includes the end position.

Example Output for MACS

MACS output

Copyright

The original MACS program is available under the terms of the Artistic License at Harvard.
Copyright (c) 2008 Yong Zhang, Tao Liu (taoliu@jimmy.harvard.edu)
The MACS2 program is available under the terms of the 3-clauses BSD license at https://github.com/taoliu/MACS/.
Copyright (c) 2013, Tao Liu lab at UB and Xiaole Shirley Liu lab at DFCI 
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