Alterations of clinical interest, (“actionable”) include Copy Number Alterations (CNA), but most sequencing panels and bioinformatic pipelines are optimised for detection of Single Nucleotide Variants, not informative for CNA-driven tumours. Furthermore, identifying CNA boundaries becomes clinically relevant when genes with opposing effects on drug sensitivity are involved on single CNAs. With hybridization-based enrichment methods, a sizeable fraction of reads align off-target. Our Excavator2 algorithm exploits off-target reads to call CNAs and outperforms standard, on-target read-based CNA-calling algorithms on Whole Exome Sequencing (NAR 2016 Nov 16;44(20):e154). We tested whether Excavator2 calls genome-wide CNAs using sequencing data from small, hybridization-based targeted enrichment panels.

5Genome-wide identification of actionable copy number alterations from targeted sequencing panels with Excavator2 / Mazzarella, L; D'aurizio, R; Frige, G; Guida, A; Belloni, E; Marino, E; Bernard, L; Pelicci, P; Magi, A. - In: ANNALS OF ONCOLOGY. - ISSN 0923-7534. - ELETTRONICO. - 28:(2017), pp. 0-0. [10.1093/annonc/mdx508.002]

5Genome-wide identification of actionable copy number alterations from targeted sequencing panels with Excavator2

D'aurizio, R;Magi, A
2017

Abstract

Alterations of clinical interest, (“actionable”) include Copy Number Alterations (CNA), but most sequencing panels and bioinformatic pipelines are optimised for detection of Single Nucleotide Variants, not informative for CNA-driven tumours. Furthermore, identifying CNA boundaries becomes clinically relevant when genes with opposing effects on drug sensitivity are involved on single CNAs. With hybridization-based enrichment methods, a sizeable fraction of reads align off-target. Our Excavator2 algorithm exploits off-target reads to call CNAs and outperforms standard, on-target read-based CNA-calling algorithms on Whole Exome Sequencing (NAR 2016 Nov 16;44(20):e154). We tested whether Excavator2 calls genome-wide CNAs using sequencing data from small, hybridization-based targeted enrichment panels.
2017
28
0
0
Mazzarella, L; D'aurizio, R; Frige, G; Guida, A; Belloni, E; Marino, E; Bernard, L; Pelicci, P; Magi, A
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1179836
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