What it does
callpeak is the main function of the MACS2 package. MACS identifies enriched binding sites in ChIP-seq experiments. It captures the influence of genome complexity to evaluate the significance of enriched ChIP regions, and improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation.
Inputs
MACS can be used for ChIP-Seq data (Treatment) alone, or with a Control sample with the increase of specificity (recommended).
A Treatment File is the only REQUIRED parameter for MACS. The file can be in BAM or BED format and this tool will autodetect the format using the first treatment file provided as input. If you have more than one alignment file per sample, you can select to pool them above. MACS can pool files together e.g. as -t A B C for treatment or -c A B C for control.
Both single-end and paired-end mapping results can be input and you can specify if the data is from paired-end reads above. Paired-end mapping results can be input to MACS as a single BAM file, and just the left mate (5' end) tag will be automatically kept. However, when paired-end format (BAMPE) is specified, MACS will use the real fragments inferred from alignment results for reads pileup.
Effective Genome Size
PLEASE assign this parameter to fit your needs!
It's the mappable genome size or effective genome size which is defined as the genome size which can be sequenced. Because of the repetitive features on the chromsomes, the actual mappable genome size will be smaller than the original size, about 90% or 70% of the genome size. The default hs -- 2.7e9 is recommended for UCSC human hg18 assembly. Here are all precompiled parameters for effective genome size from the MACS2 website:
hs: 2.7e9 mm: 1.87e9 ce: 9e7 dm: 1.2e8
Or see the deepTools website for updated information on calculating Effective Genome Size.
Outputs
This tool produces a BED file of narrowPeaks as default output. It can also produce additional outputs, which can be selected under the Additional Outputs option above.
- a BED file of peaks (default)
- a tabular file of peaks (compatible wih MultiQC)
- a BED file of peak summits
- two bedGraph files of scores, for treatment pileup and control lambda
- a HTML summary page
- a PDF plot (if model is built)
- a BED file of broad peaks (if Composite broad regions is selected under Advanced Options)
- a BED file of gapped peaks (if Composite broad regions is selected under Advanced Options)
Peaks BED File
The default output is the narrowPeak BED file (BED6+4 format). This contains the peak locations, together with peak summit, pvalue and qvalue. You can load it to UCSC genome browser.
Example:
1 2 3 4 5 6 7 8 9 10 chr1 840081 840400 treat1_peak_1 69 . 4.89872 10.50944 6.91052 158 chr1 919419 919785 treat1_peak_2 87 . 5.85158 12.44148 8.70936 130 chr1 937220 937483 treat1_peak_3 66 . 4.87632 10.06728 6.61759 154 Columns contain the following data:
Peaks tabular File
A tabular file which contains information about called peaks. You can open it in Excel and sort/filter using Excel functions. This file is compatible with MultiQC.
Example:
chr start end length abs_summit pileup -log10(pvalue) fold_enrichment -log10(qvalue) name chr1 840082 840400 319 840240 4.00 10.50944 4.89872 6.91052 treat1_peak_1 chr1 919420 919785 366 919550 5.00 12.44148 5.85158 8.70936 treat1_peak_2 chr1 937221 937483 263 937375 4.00 10.06728 4.87632 6.61759 treat1_peak_3 Columns contain the following data:
Note that these tabular file coordinates are 1-based which is different than the 0-based BED format (compare the start values in the BED and tabular Example above)
Summits BED File
A BED file which contains the peak summits locations for every peaks. The 5th column in this file is -log10qvalue, the same as in the Peaks BED file. If you want to find the motifs at the binding sites, this file is recommended. The file can be loaded directly to UCSC genome browser. Remove the beginning track line if you want to analyze it by other tools.
Example:
1 2 3 4 5 chr1 840239 840240 treat1_peak_1 6.91052 chr1 919549 919550 treat1_peak_2 8.70936 chr1 937374 937375 treat1_peak_3 6.61759 Columns contain the following data:
BedGraph Files
MACS2 will output two kinds of bedGraph files if the --bdg option is selected under the Additional Outputs option above, which contain the scores for the treatment fragment pileup and control local lambda, respectively. BedGraph files can be imported into genome browsers, such as UCSC genome browser, or be converted into even smaller bigWig files. For more information on bedGraphs, see the UCSC website here.
Example:
Treatment pileup file
1 2 3 4 chr1 840146 840147 3.00000 chr1 840147 840332 4.00000 chr1 840332 840335 3.00000
Control lambda file
1 2 3 4 chr1 800953 801258 0.02536 chr1 801258 801631 0.25364 chr1 801631 801885 0.99858 Columns contain the following data:
Broad peaks File
If the broad option (--broad) is selected unded Advanced Options above, MACS2 will output a broadPeaks file. When this flag is on, MACS will try to composite broad regions in BED12 ( a gene-model-like format ) by putting nearby highly enriched regions into a broad region with loose cutoff. The broad region is controlled by another cutoff through --broad-cutoff. The maximum length of broad region length is 4 times of d from MACS. The broad peaks file is in BED6+3 format which is similar to the narrowPeak file, except for missing the 10th column for annotating peak summits.
Example:
1 2 3 4 5 6 7 8 9 chr1 840081 840400 treat1_peak_1 52 . 4.08790 8.57605 5.21506 chr1 919419 919785 treat1_peak_2 56 . 4.37270 8.90436 5.60462 chr1 937220 937483 treat1_peak_3 48 . 4.02343 8.06676 4.86861
Columns contain the following data:
Gapped peaks File
If the broad option (--broad) is selected unded Advanced Options above, MACS2 will also output a gappedPeaks file. The gappedPeak file is in BED12+3 format and contains both the broad region and narrow peaks. The file can be loaded directly to UCSC genome browser.
Example:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 chr1 840081 840400 treat1_peak_1 52 . 840081 840400 0 1 319 0 4.08790 8.57605 5.21506 chr1 919419 919785 treat1_peak_2 56 . 919419 919785 0 1 366 0 4.37270 8.90436 5.60462 chr1 937220 937483 treat1_peak_3 48 . 937220 937483 0 1 263 0 4.02343 8.06676 4.86861
Columns contain the following data:
More Information
MACS2 performs the following analysis steps:
- Artificially extends reads to expected fragment length, and generates coverage map along genome.
- Assumes background reads are Poisson distributed. Mean of the Poisson is locally variable and is estimated from control experiment (if available) in 5Kbp or 10Kbp around examined location.
- For a given location, asks do we see more reads than we would have expected from the Poisson (p < 0.00005)? If Yes, MACS2 calls a peak.
Tips of fine-tuning peak calling
Check out these other MACS2 tools:
- MACS2 bdgcmp can be used on the callpeak bedGraph files or bedGraph files from other resources to calculate score track.
- MACS2 bdgpeakcall can be used on the file generated from bdgcmp or bedGraph file from other resources to call peaks with given cutoff, maximum-gap between nearby mergable peaks and minimum length of peak. bdgbroadcall works similarly to bdgpeakcall, however it will output a broad peaks file in BED12 format.
- Differential calling tool MACS2 bdgdiff, can be used on 4 bedGraph files which are scores between treatment 1 and control 1, treatment 2 and control 2, treatment 1 and treatment 2, treatment 2 and treatment 1. It will output the consistent and unique sites according to parameter settings for minimum length, maximum gap and cutoff.
If MACS2 fails, it is usually because it cannot build the model for peaks. You may want to extend mfold range by increasing the upper bound or play with Build model options. For more information, see the MACS2 website.
Integration of MACS2 with Galaxy performed by Ziru Zhou and Bjoern Gruening.