Mutational Signatures (abbreviated as mtsg) finds and quantifies COSMIC mutational signatures across samples.
mtsg uses a base set of mutational signatures extracted by SigProfiler for single-base substitutions (SBS), i.e., single-nucleotide variants (SNV), using 2780 whole-genome variant calls from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project.
|VCF(s)||Array of files||One or more VCF sources. The files can be either uncompressed or gzipped.||[
|Genome build||String||The genome build used as reference. [default: "GRCh38"]||GRCh38|
Mutational Signatures only requires VCFs as inputs. All other inputs are optional.
VCF(s) is a list of VCF inputs. The inputs are expected to be single-sample and uncompressed or gzipped. The basename of the filename is used as the sample name.
|Raw signature activities||File||A tab-delimited file of the raw results with signature activities per sample|
|Signature activities visualization||File||HTML file for interactive plotting|
Creating a workspace¶
Before you can run one of our workflows, you must first create a workspace in DNAnexus for the run. Refer to the general workflow guide to learn how to create a DNAnexus workspace for each workflow run.
You can navigate to the Mutational Signatures workflow page here.
Uploading Input Files¶
Mutational Signatures requires at least one VCF to be uploaded.
Refer to the general workflow guide to learn how to upload input files to the workspace you just created.
Running the Workflow¶
Refer to the general workflow guide to learn how to launch the workflow, hook up input files, adjust parameters, start a run, and monitor run progress.
Analysis of Results¶
Each tool in St. Jude Cloud produces a visualization that makes understanding results more accessible than working with spreadsheets or tab-delimited files. This is the primary way we recommend you work with your results.
Refer to the general workflow guide to learn how to access these visualizations.
We also include the raw output files for you to dig into if the visualization is not sufficient to answer your research question.
Refer to the general workflow guide to learn how to access raw results files.
Upon a successful run of Mutational Signatures, two files are saved to the results directory: raw signature activities and a visualization file.
Raw signature activities¶
Raw signature activities is a tab-delimited file of the raw results with the signature activity counts for each input sample . Column 1 is the SBS signature identifier, and columns 2 through N are the counts of signature matches for each input sample. Signatures that have no matches across all samples are omitted.
Signature activities visualization¶
Signature activities visualization is an HTML file that can be used for interactive plotting.
When opened in a web browser, multiple sections of (stacked) bar charts are presented: Cohort Signature Contribution Means, Sample Signature Contributions, and Sample Signature Activities.
The Cohort Signature Contribution Means section has proportion of SNVs of a mutational signature for an entire cohort. The reference cohort can be further divided into categories, selectable in the reference dropdown. Click on the tick labels to toggle between reference and query samples. Hover over a stacked bar to display the absolute count, signature name, and etiology.
The Sample Signature Contributions section shows the proportion of SNVs of a mutational signature for a single sample. Like the Cohort Signature Contribution Means section, each stacked bar can be hovered over to display the absolute count, the signature name, and etiology.
Each sample has a total mutation burden, which is shown in the Sample Signature Activities section. This is the factor used to sort the samples, i.e, in descending total mutational burden order.
At the bottom is the legend, which shows any mutational signature present in either the reference or query cohort. The legend item may have a proposed etiology and, when clicked, opens that mutational signature on COSMIC Mutational Signatures.
Frequently asked questions¶
None yet! If you have any questions not covered here, feel free to reach out on our contact form.
Alexandrov, L.B., Kim, J., Haradhvala, N.J. et al. The repertoire of mutational signatures in human cancer. Nature 578, 94–101 (2020). https://doi.org/10.1038/s41586-020-1943-3
Bergstrom, E.N., Huang, M.N., Mahto, U. et al. SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events. BMC Genomics 20, 685 (2019). https://doi.org/10.1186/s12864-019-6041-2