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Quantification of aneuploidy in targeted sequencing data using ASCETS

Liam F. Spurr, Mehdi Touat, Alison M. Taylor, Adrian M. Dubuc, Juliann Shih, David M. Meredith, William Pisano, Matthew L Meyerson, Keith L. Ligon, Andrew D. Cherniack, Yvonne Y. Li, Rameen Beroukhim

2020Bioinformatics58 citationsDOIOpen Access PDF

Abstract

SUMMARY: The expansion of targeted panel sequencing efforts has created opportunities for large-scale genomic analysis, but tools for copy-number quantification on panel data are lacking. We introduce ASCETS, a method for the efficient quantitation of arm and chromosome-level copy-number changes from targeted sequencing data. AVAILABILITY AND IMPLEMENTATION: ASCETS is implemented in R and is freely available to non-commercial users on GitHub: https://github.com/beroukhim-lab/ascets, along with detailed documentation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Topics & Concepts

Computer scienceDocumentationMassive parallel sequencingCopy-number variationAneuploidyDNA sequencingChromosomeComputational biologyData miningBiologyGenomeGeneticsDNAOperating systemGeneGenomic variations and chromosomal abnormalitiesGenetic Associations and EpidemiologyMicrotubule and mitosis dynamics
Quantification of aneuploidy in targeted sequencing data using ASCETS | Litcius