Package: sigProfilerPlotting
SigProfilerPlottingSigProfilerPlotting provides a standard tool for displaying all types of mutational signatures as well as all types of mutational patterns in cancer genomes. The tool seamlessly integrates with other SigProfiler tools.INTRODUCTIONThe purpose of this document is to provide a guide for using the SigProfilerPlotting framework and associated functions/tools to visualize the output from SigProfilerExtraction and SigProfilerSimulator. An extensive Wiki page detailing the usage of this tool can be found athttps://osf.io/2aj6t/wiki/home.For users that prefer working in an R environment, a wrapper package is provided and can be found and installed from:https://github.com/AlexandrovLab/SigProfilerPlottingRPREREQUISITESThe framework is written in PYTHON, however, it also requires the following software with the given versions (or newer):PYTHON          version 3.4 or newerSigProfilerMatrixGenerator (recommended)QUICK START GUIDEThis section will guide you through the minimum steps required to plot mutational matrices:Install the python package using pip:pip install SigProfilerPlottingPlot mutational matrices from a Python session or using the Command Line Interface (CLI) as follows:Using the Python session, the command is as follows:$python3>>importsigProfilerPlottingassigPlt>>sigPlt.plotSBS(matrix_path,output_path,project,plot_type,percentage=False)The required parameters are:sigPlt.plotSBS(matrix_path, output_path, project, plot_type)Using the CLI, the command is as follows:SigProfilerPlottingplotSBS<matrix_path><output_path><project><plot_type>The final plots are saved into the user-provided output folder.Single Base Substitution, Double Base Substitution, and Indel PlottingAVAILABLE FUNCTIONSimportsigProfilerPlottingassigPltsigPlt.plotSBS(matrix_path,output_path,project,plot_type,percentage=False)sigPlt.plotDBS(matrix_path,output_path,project,plot_type,percentage=False)sigPlt.plotID(matrix_path,output_path,project,plot_type,percentage=False)Copy Number and Structural Variant PlottingimportsigProfilerPlottingassigPltmatrix_path="./sigProfilerPlotting/examples/input/breast_cancer_samples_example.CNV48.all"#Output of CNVMatrixGeneratoroutput_path="./sigProfilerPlotting/examples/output/"project="Breast"AVAILABLE FUNCTIONSMulti-page pdf of CNV or SV signaturessigPlt.plotCNV(matrix_path,output_path,project,percentage=True,aggregate=False)#plotting of CNV signaturessigPlt.plotSV(matrix_path,output_path,project,percentage=True,aggregate=False)#plotting of SV signaturesMulti-page pdf of CNV or SV countssigPlt.plotCNV(matrix_path,output_path,project,percentage=False,aggregate=False)#plotting of CNV countssigPlt.plotSV(matrix_path,output_path,project,percentage=False,aggregate=False)#plotting of SV countsSingle pdf of CNV or SV counts per sample for a given cancer type/projectsigPlt.plotCNV(matrix_path,output_path,project,percentage=False,aggregate=True)#plotting of CNV countssigPlt.plotSV(matrix_path,output_path,project,percentage,aggregate=True)#plotting of SV countsmatrix_path -> path to the mutational matrix of interestoutput_path -> desired output pathproject -> name of unique sample setplot_type -> context of the mutational matrix (96, 192, 78, 94, etc.)percentage -> Boolean: plot the mutational matrix as percentages of the sample's total mutation count. Default is FalseTo create a sample portrait, ensure that you have a matrix for all required contexts (SBS-6, SBS-24, SBS-96, SBS-384, SBS-1536, DBS-78, DBS-312, ID-83, ID-28, ID-96)fromsigProfilerPlottingimportsample_portraitassPsP.samplePortrait(sample_matrices_path,output_path,project,percentage=False)EXAMPLEThis package comes with an example test for each plot type. Run the script plot_example.py from within the examples directory in the downloaded repo after installation:python3sigProfilerPlotting/examples/plot_example.pyThis example will create plots for each context for each of the included four samples. These plots will be saved within thesigProfilerPlotting/examples/output/folder.CITATIONBergstrom EN, Huang MN, Mahto U, Barnes M, Stratton MR, Rozen SG, Alexandrov LB: SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events. BMC Genomics 2019, 20:685https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-019-6041-2COPYRIGHTCopyright (c) 2020, Erik Bergstrom [Alexandrov Lab] All rights reserved.Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.CONTACT INFORMATIONPlease address any queries or bug reports to Erik Bergstrom atebergstr@eng.ucsd.edu