ascatNgs: Identifying Somatically Acquired Copy-Number Alterations from Whole-Genome Sequencing Data

Area of Science:

• Genomics
• Bioinformatics
• Cancer Research

Background:

• Allele-Specific Copy number Analysis of Tumours (ASCAT) is crucial for understanding tumor genome alterations.
• ASCAT identifies DNA copy number changes and estimates Aberrant Cell Fraction (ACF).
• The ASCAT R-package requires extensive file management, posing a challenge for researchers.

Purpose of the Study:

• To introduce ascatNgs, a novel suite of tools designed to streamline the ASCAT workflow.
• To simplify the generation and handling of necessary file types for ASCAT analysis.
• To provide flexible computational approaches for both individual and large-scale tumor genome analyses.

Main Methods:

• Development of a user-friendly tool suite, ascatNgs.
• Integration of functionalities for handling ASCAT-required file types.
• Implementation of 'one-shot' execution and scalable solutions for compute farms.

Main Results:

• ascatNgs facilitates easier implementation of ASCAT for tumor DNA analysis.
• The tool suite simplifies complex data handling, reducing user burden.
• Code is publicly available on GitHub, promoting accessibility and collaboration.

Conclusions:

• ascatNgs significantly enhances the usability of ASCAT for researchers.
• The developed tools support diverse research needs, from single samples to large cohorts.
• This contributes to advancing cancer genomics research through improved analytical pipelines.