# multiBigwigSummary¶

Given typically two or more bigWig files, multiBigwigSummary computes the average scores for each of the files in every genomic region. This analysis is performed for the entire genome by running the program in bins mode, or for certain user selected regions in BED-file mode. Most commonly, the default output of multiBigwigSummary (a compressed numpy array, .npz) is used by other tools such as plotCorrelation or plotPCA for visualization and diagnostic purposes.

Note that using a single bigWig file is only recommended if you want to produce a bedGraph file (i.e., with the --outRawCounts option; the default output file cannot be used by ANY deepTools program if only a single file was supplied!).

A detailed sub-commands help is available by typing:

multiBigwigSummary bins -h

multiBigwigSummary BED-file -h

usage: multiBigwigSummary [-h] [--version]  ...


## Named Arguments¶

 –version show program’s version number and exit

## commands¶

 Possible choices: bins, BED-file

## Sub-commands:¶

### bins¶

The average score is based on equally sized bins (10 kilobases by default), which consecutively cover the entire genome. The only exception is the last bin of a chromosome, which is often smaller. The output of this mode is commonly used to assess the overall similarity of different bigWig files.

multiBigwigSummary -b file1.bw file2.bw -out results.npz


#### Required arguments¶

 –bwfiles, -b List of bigWig files, separated by spaces. –outFileName, -out File name to save the compressed matrix file (npz format)needed by the “plotHeatmap” and “plotProfile” tools.

#### Optional arguments¶

 –labels, -l User defined labels instead of default labels from file names. Multiple labels have to be separated by spaces, e.g., –labels sample1 sample2 sample3 –chromosomesToSkip List of chromosomes that you do not want to be included. Useful to remove “random” or “extra” chr. –binSize, -bs Size (in bases) of the windows sampled from the genome. –distanceBetweenBins, -n By default, multiBigwigSummary considers adjacent bins of the specified –binSize. However, to reduce the computation time, a larger distance between bins can be given. Larger distances results in fewer considered bins. –version show program’s version number and exit –region, -r Region of the genome to limit the operation to - this is useful when testing parameters to reduce the computing time. The format is chr:start:end, for example –region chr10 or –region chr10:456700:891000. –blackListFileName, -bl A BED or GTF file containing regions that should be excluded from all analyses. Currently this works by rejecting genomic chunks that happen to overlap an entry. Consequently, for BAM files, if a read partially overlaps a blacklisted region or a fragment spans over it, then the read/fragment might still be considered. Please note that you should adjust the effective genome size, if relevant. –numberOfProcessors, -p Number of processors to use. Type “max/2” to use half the maximum number of processors or “max” to use all available processors. –verbose, -v Set to see processing messages.

#### Output optional options¶

 –outRawCounts Save average scores per region for each bigWig file to a single tab-delimited file.

#### deepBlue arguments¶

Options used only for remote bedgraph/wig files hosted on deepBlue

 –deepBlueURL For remote files bedgraph/wiggle files hosted on deepBlue, this specifies the server URL. The default is “http://deepblue.mpi-inf.mpg.de/xmlrpc”, which should not be changed without good reason. –userKey For remote files bedgraph/wiggle files hosted on deepBlue, this specifies the user key to use for access. The default is “anonymous_key”, which suffices for public datasets. If you need access to a restricted access/private dataset, then request a key from deepBlue and specify it here. –deepBlueTempDir If specified, temporary files from preloading datasets from deepBlue will be written here (note, this directory must exist). If not specified, where ever temporary files would normally be written on your system is used. –deepBlueKeepTemp If specified, temporary bigWig files from preloading deepBlue datasets are not deleted. A message will be printed noting where these files are and what sample they correspond to. These can then be used if you wish to analyse the same sample with the same regions again.

### BED-file¶

The user provides a BED file that contains all regions that should be considered for the analysis. A common use is to compare scores (e.g. ChIP-seq scores) between different samples over a set of pre-defined peak regions.

multiBigwigSummary -b file1.bw file2.bw -out results.npz --BED selection.bed


#### Required arguments¶

 –bwfiles, -b List of bigWig files, separated by spaces. –outFileName, -out File name to save the compressed matrix file (npz format)needed by the “plotHeatmap” and “plotProfile” tools. –BED Limits the analysis to the regions specified in this file.

#### Optional arguments¶

 –labels, -l User defined labels instead of default labels from file names. Multiple labels have to be separated by spaces, e.g., –labels sample1 sample2 sample3 –chromosomesToSkip List of chromosomes that you do not want to be included. Useful to remove “random” or “extra” chr. –version show program’s version number and exit –region, -r Region of the genome to limit the operation to - this is useful when testing parameters to reduce the computing time. The format is chr:start:end, for example –region chr10 or –region chr10:456700:891000. –blackListFileName, -bl A BED or GTF file containing regions that should be excluded from all analyses. Currently this works by rejecting genomic chunks that happen to overlap an entry. Consequently, for BAM files, if a read partially overlaps a blacklisted region or a fragment spans over it, then the read/fragment might still be considered. Please note that you should adjust the effective genome size, if relevant. –numberOfProcessors, -p Number of processors to use. Type “max/2” to use half the maximum number of processors or “max” to use all available processors. –verbose, -v Set to see processing messages.

#### Output optional options¶

 –outRawCounts Save average scores per region for each bigWig file to a single tab-delimited file.

#### GTF/BED12 options¶

 –metagene When either a BED12 or GTF file are used to provide regions, perform the computation on the merged exons, rather than using the genomic interval defined by the 5-prime and 3-prime most transcript bound (i.e., columns 2 and 3 of a BED file). If a BED3 or BED6 file is used as input, then columns 2 and 3 are used as an exon. –transcriptID When a GTF file is used to provide regions, only entries with this value as their feature (column 2) will be processed as transcripts. –exonID When a GTF file is used to provide regions, only entries with this value as their feature (column 2) will be processed as exons. CDS would be another common value for this. –transcript_id_designator Each region has an ID (e.g., ACTB) assigned to it, which for BED files is either column 4 (if it exists) or the interval bounds. For GTF files this is instead stored in the last column as a key:value pair (e.g., as ‘transcript_id “ACTB”’, for a key of transcript_id and a value of ACTB). In some cases it can be convenient to use a different identifier. To do so, set this to the desired key.

#### deepBlue arguments¶

Options used only for remote bedgraph/wig files hosted on deepBlue

 –deepBlueURL For remote files bedgraph/wiggle files hosted on deepBlue, this specifies the server URL. The default is “http://deepblue.mpi-inf.mpg.de/xmlrpc”, which should not be changed without good reason. –userKey For remote files bedgraph/wiggle files hosted on deepBlue, this specifies the user key to use for access. The default is “anonymous_key”, which suffices for public datasets. If you need access to a restricted access/private dataset, then request a key from deepBlue and specify it here. –deepBlueTempDir If specified, temporary files from preloading datasets from deepBlue will be written here (note, this directory must exist). If not specified, where ever temporary files would normally be written on your system is used. –deepBlueKeepTemp If specified, temporary bigWig files from preloading deepBlue datasets are not deleted. A message will be printed noting where these files are and what sample they correspond to. These can then be used if you wish to analyse the same sample with the same regions again.

example usage:
multiBigwigSummary bins -b file1.bw file2.bw -out results.npz

multiBigwigSummary BED-file -b file1.bw file2.bw -out results.npz –BED selection.bed

## Example¶

In the following example, the average values for our test ENCODE ChIP-Seq datasets are computed for consecutive genome bins (default size: 10kb) by using the bins mode.

$deepTools2.0/bin/multiBigwigSummary bins \ -b testFiles/H3K4Me1.bigWig testFiles/H3K4Me3.bigWig testFiles/H3K27Me3.bigWig testFiles/Input.bigWig \ --labels H3K4me1 H3K4me3 H3K27me3 input \ -out scores_per_bin.npz --outRawCounts scores_per_bin.tab$ head scores_per_bin.tab
#'chr'  'start' 'end'   'H3K4me1'       'H3K4me3'       'H3K27me3'      'input'
19      0       10000   0.0     0.0     0.0     0.0
19      10000   20000   0.0     0.0     0.0     0.0
19      20000   30000   0.0     0.0     0.0     0.0
19      30000   40000   0.0     0.0     0.0     0.0
19      40000   50000   0.0     0.0     0.0     0.0
19      50000   60000   0.0221538461538 0.0     0.00482142857143        0.0522717391304
19      60000   70000   4.27391282051   1.625   0.634116071429  1.29124347826
19      70000   80000   13.0891675214   24.65   1.8180625       2.80073695652
19      80000   90000   1.74591965812   0.29    4.35576785714   0.92987826087


To compute the average values for a set of genes, use the BED-file mode.

$deepTools2.0/bin/multiBigwigSummary BED-file \ --bwfiles testFiles/*bigWig \ --BED testFiles/genes.bed \ --labels H3K27me3 H3K4me1 H3K4me3 HeK9me3 input \ -out scores_per_transcript.npz --outRawCounts scores_per_transcript.tab$ head scores_per_transcript.tab
#'chr'     'start' 'end'   'H3K27me3'      'H3K4me1'       'H3K4me3'       'HeK9me3'       'input'
19  60104   70951   0.663422099099  4.37103606574   14.9609108509   0.596631607217  1.34274297191
19  60950   70966   0.714223982699  4.54650763906   16.2336261981   0.62173674295   1.41719308888
19  62114   70944   0.747578769617  4.84009060023   18.2951302378   0.648723472352  1.51324474371
19  63820   70951   0.781816722009  5.30500631048   22.5579862572   0.682862029229  1.55490104062
19  65057   66382   0.528301886792  5.45886792453   0.523018867925  0.555471698113  1.97056603774
19  65821   66416   0.411764705882  3.0     0.636974789916  0.168067226891  1.67226890756
19  65821   70945   0.844600775761  4.79176424668   31.1346604215   0.693073728066  1.47911787666
19  66319   66492   0.774566473988  1.59537572254   0.0     0.0     0.578034682081
19  66345   71535   0.877430197151  5.49036608863   43.978805395    0.746026011561  1.43545279383


The default output of multiBamSummary (a compressed numpy array: *.npz) can be visualized using plotCorrelation or plotPCA.

The optional output (--outRawCounts) is a simple tab-delimited file that can be used with any other program. The first three columns define the region of the genome for which the reads were summarized.

## multiBigwigSummary in Galaxy¶

Below is the screenshot showing how to use multiBigwigSummary on the deeptools galaxy.