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An R wrapper for SigProfilerExtractor that allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use o…
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An R wrapper for running the SigProfilerExtractor framework.


The purpose of this document is to provide a guide for using the SigProfilerExtractor framework to extract the De Novo mutational signatures from a set of samples and decompose the De Novo signatures into the COSMIC signatures. An extensive Wiki page detailing the usage of this tool can be found at

For users that prefer working in a Python environment, the tool is written in Python and can be found and installed from:


devtools (R)

>> install.packages("devtools")

reticulate* (R)

>> install.packages("reticulate")  

*Reticulate has a known bug of preventing python print statements from flushing to standard out. As a result, some of the typical progress messages are delayed.


This section will guide you through the minimum steps required to extract mutational signatures from genomes:

  1. First, install the python package using pip. The R wrapper still requires the python package:
                          pip install sigproextractor
  1. Open an R session and ensure that your R interpreter recognizes the path to your python installation:
$ R
>> library("reticulate")
>> use_python("path_to_your_python")
>> py_config()
python:         /anaconda3/bin/python
libpython:      /anaconda3/lib/libpython3.6m.dylib
pythonhome:     /anaconda3:/anaconda3
version:        3.6.5 |Anaconda, Inc.| (default, Apr 26 2018, 08:42:37)  [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]
numpy:          /anaconda3/lib/python3.6/site-packages/numpy
numpy_version:  1.16.1

If you do not see your python path listed, restart your R session and rerun the above commands in order.

  1. Install SigProfilerExtractorR using devtools:
  1. Load the package in the same R session and install your desired reference genome as follows (available reference genomes are: GRCh37, GRCh38, mm9, and mm10):
>> library("SigProfilerExtractorR")
>> install("GRCh37", rsync=FALSE, bash=TRUE)

This will install the human 37 assembly as a reference genome.


Information about supported will be found at

Extraction Signatures

Signatures can be extracted from vcf files or tab delimited mutational table using the sigprofilerextractor function.

>> help(sigprofilerextractor)

This will show the details about the sigprofilerextractor funtion.


>> library("SigProfilerExtractorR")
>> path_to_example_data <- importdata("table")
>> data <- path_to_example_data # here you can provide the path of your own data
>> sigprofilerextractor("table", "example_output", data, minsigs=1, maxsigs=3, replicates=10, cpu=-1)

The example file will generated in the working directory

Decomposition of signatures to COSMIC signatures

SigProfilerExtractorR offer a separate function, decomposition, that decomposes a tab delimited file containing a set of De Novo signatures to the COSMIC signatures and attribute them to a given set of sample.


This will show the details about the decomposition function.


This software and its documentation are copyright 2018 as a part of the sigProfiler project. The SigProfilerExtractor framework is free software and is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.


Please address any queries or bug reports to S M Ashiqul Islam (Mishu) at

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