C2Rdiff

C2Rdiff is a software package designed for differential copy number analysis from sequencing data. It aims to identify genomic regions where copy number differs significantly between samples or conditions by comparing read depth signals.

The typical workflow starts with aligned sequencing data (BAM/CRAM) for multiple samples and a reference genome. C2Rdiff computes read-depth signals across the genome, then applies normalization to correct for factors such as sequencing depth, GC content, and mappability. The genome is segmented into regions of similar copy number, and statistical tests compare these regions between conditions to produce differential CNV calls, usually reporting fold changes and p-values or false discovery rates.

Outputs generally include a list of differential CNV regions with coordinates, estimated copy-number states, and associated statistics, along with optional visualization plots. The software supports multi-sample analysis, batch effect considerations, and tumor-normal pair comparisons, and is designed to integrate with common formats such as BED and VCF for downstream workflows. C2Rdiff is typically accessible via a command-line interface, with some versions offering programmatic APIs or workflow-manager compatibility.

Implementation and availability: C2Rdiff is released as open-source software under a compatible license and is maintained by a research group or community contributing to its development. Documentation usually covers installation, data preparation, parameter guidance, and interpretation of results. Use cases include cancer genomics to detect somatic CNVs and germline CNV studies in comparative genomics, with results best validated by orthogonal methods.

Limitations: reliable results require adequate sequencing depth and appropriate controls. Results can be confounded by tumor purity, ploidy, complex rearrangements, and sample quality. Users should assess underlying assumptions and perform benchmarking before drawing biological conclusions.