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computeMatrix (version 3.5.4+galaxy0)
Select regions
Select regions 0
By default, the order of samples given to the program is dependent on their order in your history. If the order of the samples is vital to you, select Yes below.
You can generate a bigWig file from a BAM/CRAM file using the bamCoverage tool.
By default, the names of the samples in your history are used.
In the scale-regions mode, all regions in the BED file are stretched or shrunken to the same length (in bases) that is indicated by the user. Reference-point refers to a position within the BED regions (start or end of each region). In the reference-point mode only those genomic positions before (upstream) and/or after (downstream) the reference point will be considered.

What it does

This tool prepares an intermediate file (a gzipped table of values) that contains scores associated with genomic regions. The regions can either be scaled to the same size (using the scale-regions mode) or you can choose the start, end, or center of each region as the focus point for the score calculations. For more details, check out the explanation here.

The intermediate file produced by computeMatrix is meant to be used with plotHeatmap and plotProfile. See the descriptions of plotHeatmap and plotProfile for example plots.

Relationship between computeMatrix, heatmapper and profiler

Usage hints

The supplied genomic regions can really be anything - genes, parts of genes, ChIP-seq peaks, favorite genome regions... as long as you provide a proper file in BED or INTERVAL format. If you would like to compare different groups of regions (e.g., genes from chromosome 2 and 3), you can supply more than 1 regions file, one for each group by selecting "Insert Select regions".


You can select as many score (bigWig) files as you like. Simply use the Shift and/or Command key while clicking on the files of interest.


The multitude of parameters can seem daunting at first - here are the options that we tend to tune most often:

  • bin Size -- The default value works well most of the time, but if you want to have a more finely grained image, decrease the default value (but not smaller than your bigWig file(s)' bin size). If you want to reduce the computation time, increase it.
  • Skip zeros -- useful to avoid completely blank lines in the heatmap.
  • Convert missing values to 0? -- If you want to identify clusters of similar regions in an unsupervised fashion using plotHeatmap and/or plotProfile, you should definitely set this to 'yes'.

Output files

The default output is a gzipped table of values that is used by both plotHeatmap and plotProfile.

The optional output files include a) the regions after sorting and filtering (if selected) as they were used to calculate the values for the plotting, and b) the uncompressed table that underlies the heatmap.

TIP: computeMatrix can also be used to filter and sort regions according to their score by making use of the "advanced output settings".

/repository/static/images/2583e03248719a3f/computeMatrix_advancedOutput.png /repository/static/images/2583e03248719a3f/computeMatrix_output.png

Note that these advanced output options are available for plotHeatmap and plotProfile, too.

See the following table for the optional output options:

optional output type computeMatrix plotHeatmap plotProfile
values underlying the heatmap yes yes no
values underlying the profile no no yes
sorted and/or filtered regions yes yes yes

More examples can be found in our Gallery.

For more information on the tools, please visit our help site.

For support or questions please post to Biostars. For bug reports and feature requests please open an issue on github.

This tool is developed by the Bioinformatics and Deep-Sequencing Unit at the Max Planck Institute for Immunobiology and Epigenetics.