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AlexandrovLab / SigProfilerAssignment

Assignment of known mutational signatures to individual samples and individual somatic mutations
BSD 2-Clause "Simplified" License
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please rerun by setting the flag "collapse_to_SBS96 = False " #127

Closed YingYa closed 4 months ago

YingYa commented 4 months ago

Hi,

I run SigProfilerAssignment (v0.1.6) using Command Line Interface, but failed to set "collapse_to_SBS96 = False".

SigProfilerAssignment cosmic_fit --genome_build GRCh38 --cosmic_version 3.4 --collapse_to_SBS96 False --input_type matrix --context_type 48 --export_probabilities_per_mutation True Cancer.CNV48.matrix.tsv COSMIC_fitting_cnv/

-------Python and Package Versions------- Python Version: 3.9.19 SigProfilerPlotting Version: 1.3.23 SigProfilerMatrixGenerator Version: 1.2.26 SigProfilerAssignment Version: 0.1.6 Pandas version: 1.5.3 Numpy version: 1.25.2

--------------EXECUTION PARAMETERS-------------- INPUT DATA input_type: matrix output: COSMIC_fitting_cnv/ samples: Cancer.CNV48.matrix.tsv reference_genome: GRCh38 context_types: 48 exome: False COSMIC MATCH cosmic_version: 3.4 nnls_add_penalty: 0.05 nnls_remove_penalty: 0.01 initial_remove_penalty: 0.05 de_novo_fit_penalty: 0.02 export_probabilities: True collapse_to_SBS96: True denovo_refit_option: False decompose_fit_option: False cosmic_fit_option: True

mdbarnesUCSD commented 4 months ago

Hi @YingYa,

Thanks for trying out the CLI and identifying this issue with how arguments are handled. We will address this in the upcoming release.