SigProfilerAssignment 0.0.3

Mutational signatures attribution and decomposition tool

SigProfilerAssignment

SigProfilerAssignment is a new mutational attribution and decomposition tool that performs the following functions:

• Attributing a known set of mutational signatures to an individual sample or multiple samples.
• Decomposing de novo signatures to COSMIC signature database.
• Attributing COSMIC database or a custom signature database to given samples.

The tool identifies the activity of each signature in the sample and assigns the probability for each signature to cause a specific mutation type in the sample. The tool makes use of SigProfilerMatrixGenerator, SigProfilerExtractor and SigProfilerPlotting.

Installs

for installing from PyPi in new conda environment

$ pip install SigProfilerAssignment

Installing this package : git clone this repo or download the zip file. Unzip the contents of SigProfilerExtractor-master.zip or the zip file of a corresponding branch.

$ cd SigProfilerAssignment-master
$ pip install .

Decomposes the De Novo Signatures into COSMIC Signatures and assigns COSMIC signatures into samples

Decompose Fit

from SigProfilerAssignment import Analyzer as Analyze
Analyze.decompose_fit(samples,  output, signatures=None, signature_database=None,genome_build="GRCh37",  make_decomposition_plots=True, collapse_to_SBS96=True,connected_sigs=True, verbose=False)

De Novo Fit

from SigProfilerAssignment import Analyzer as Analyze
Analyze.denovo_fit(samples,  output, signatures=None, signature_database=None,genome_build="GRCh37",  make_decomposition_plots=True, collapse_to_SBS96=True,connected_sigs=True, verbose=False)

Cosmic Fit

from SigProfilerAssignment import Analyzer as Analyze
Analyze.cosmic_fit(samples,  output, signatures=None, signature_database=None,genome_build="GRCh37",  make_decomposition_plots=True, collapse_to_SBS96=True,connected_sigs=True, verbose=False)

Parameters

Parameter	Variable Type	Parameter Description
signatures	String	Path to a tab delimited file that contains the signaure table where the rows are mutation types and colunms are signature IDs.
activities	String	Path to a tab delimilted file that contains the activity table where the rows are sample IDs and colunms are signature IDs.
samples	String	Path to a tab delimilted file that contains the activity table where the rows are mutation types and colunms are sample IDs.
output	String	Path to the output folder.
genome_build	String	The genome type. Example: "GRCh37", "GRCh38", "mm9", "mm10". The default value is "GRCh37"
verbose	Boolean	Prints statements. Default value is False.

SPA analysis Example

#import modules
import SigProfilerAssignment as spa
from SigProfilerAssignment import Analyzer as Analyze

#set directories and paths to signatures and samples
dir_inp = spa.__path__[0]+'/data/Examples/'
signatures = dir_inp+"Results_scenario_8/SBS96/All_Solutions/SBS96_3_Signatures/Signatures/SBS96_S3_Signatures.txt"
activities=dir_inp+"Results_scenario_8/SBS96/All_Solutions/SBS96_3_Signatures/Activities/SBS96_S3_NMF_Activities.txt"
samples=dir_inp+"Input_scenario_8/Samples.txt"
output="output_example/"
sigs= "COSMIC_v3_SBS_GRCh37_noSBS84-85.txt" #Custom Signature Database

#Analysis of SP Assignment 
Analyze.cosmic_fit( samples, output, signatures=None,signature_database=sigs,genome_build="GRCh37", verbose=False)

Copyright

This software and its documentation are copyright 2022 as a part of the SigProfiler project. The SigProfilerAssignment 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.

Contact Information

Please address any queries or bug reports to Raviteja Vangara at [e-mail]