Denovo fit of SV signatures

[Avramis]

I tried to use the following command to decompose_fit to decompose SV signatures that were extracted from SigprofilerExtractor to a given SV reference database

_from SigProfilerAssignment import Analyzer as Analyze
samples = "/Users/avraam/Desktop/NigData/SV_Matrices/Data.SV32.matrix.tsv"
output = "/Users/avraam/Desktop/NigData/Testing/"
sigs_DB = "Users/avraam/Desktop/NigData/RearrangmentSigsDB/RefSigv1_Rearr.tsv"
denovo_extracted_sigs = "/Users/avraam/Desktop/NigData/SigProResults2Check3/SV32/All_Solutions/SBSSV_7_Signatures/Signatures/SBSSV_S7_Signatures.txt"

Analyze.decompose_fit(samples,
output,
signatures=denovo_extracted_sigs,
signature_database=sigs_DB,
genome_build="GRCh38",
verbose=False,
new_signature_thresh_hold=0.8,
exclude_signature_subgroups=None,
exome=False)_

I got the following error

Decomposing De Novo Signatures .....
Traceback (most recent call last):
File "", line 1, in
File "/Users/avraam/Downloads/SigProfilerAssignment-main/SigProfilerAssignment/Analyzer.py", line 5, in decompose_fit
decomp.spa_analyze(samples=samples, output=output, signatures=signatures, signature_database=signature_database,nnls_add_penalty=nnls_add_penalty, nnls_remove_penalty=nnls_remove_penalty, initial_remove_penalty=initial_remove_penalty,genome_build=genome_build, cosmic_version=cosmic_version, make_plots=make_plots, collapse_to_SBS96=collapse_to_SBS96,connected_sigs=connected_sigs, verbose=verbose,decompose_fit_option= True,denovo_refit_option=False,cosmic_fit_option=False,devopts=devopts,new_signature_thresh_hold=new_signature_thresh_hold,exclude_signature_subgroups=exclude_signature_subgroups,exome=exome,input_type=input_type,context_type=context_type,export_probabilities=export_probabilities)
File "/Users/avraam/Downloads/SigProfilerAssignment-main/SigProfilerAssignment/decomposition.py", line 354, in spa_analyze
final_signatures = sub.signature_decomposition(processAvg, mutation_type, layer_directory2, genome_build=genome_build,cosmic_version=cosmic_version,signature_database=signature_database, mutation_context=mutation_context, add_penalty=0.05, connected_sigs=connected_sigs,remove_penalty=0.01, make_decomposition_plots=make_plots, originalProcessAvg=originalProcessAvg,new_signature_thresh_hold=new_signature_thresh_hold,sig_exclusion_list=sig_exclusion_list,exome=exome, m_for_subgroups=m_for_subgroups)
UnboundLocalError: local variable 'm_for_subgroups' referenced before assignment

After investigating the issue it seems that the m_for_subgroups is not initiated because the SV matrix does not match the any of the dimensions in the if statements (lines 104 .. 109)

I edited the decomposition.py and added the following statement in line 110
if m=='32':
m_for_subgroups = 'SV'

The code finished executing and I got an output that seem ok. However, I do not know if it breaks the code at any other parts.

[mdbarnesUCSD]

This issue has been resolved in release v0.0.18. Please reach out if you encounter other issues. Thanks!