copy-number

You can automate copy-number estimation by providing input coverage or ratio data and target bins to generate CNV segments, gene-level tables, and plots. The workflow handles segmentation, annotation, and visualization automatically.

Yes, CNV analysis supports both tumor-normal and tumor-only designs. You can process tumor-only samples by providing the appropriate coverage data and sample metadata to generate gene-level CNV tables and plots.

Provide input coverage or ratio data, target bins, and sample metadata. The workflow annotates segments to genes and recurrent regions, producing both chromosome-level and gene-centric plots alongside gene-level CNV tables.

Yes, the workflow requires and supports CNVkit-style and GATK CNV-style pipelines. It also uses pandas and matplotlib for data processing and visualization, recording reference builds and parameter settings in outputs.

You can perform cohort CNV summaries by processing sample metadata alongside coverage data. The workflow generates reporting-ready outputs, including gene-level CNV tables and recurrent region annotations across the entire cohort.

Reference builds, caller assumptions, and parameter settings are recorded in final outputs to ensure repeatable CNV results. This documentation maintains consistency across coverage-based segmentation and gene-level reporting workflows.