BioDiscovery has been estimating copy number from NGS data for many years and the algorithms have evolved and improved over the years. The BAM MSR algorithm uses a small set of “normal” samples to create a reference to estimate copy number from the samples under analysis. The algorithm uses a dynamic binning approach to derive copy number and BAF from target regions as well as the backbone and thus can be applied to a wide variety of NGS data. Here are a few publications showing the algorithm’s versatility in handling different types of NGS data from panels to whole genome.
ONCOGENE PANEL SEQUENCING ANALYSIS IDENTIFIES CANDIDATE ACTIONABLE GENES IN ADVANCED WELL-DIFFERENTIATED GASTROENTEROPANCREATIC NEUROENDOCRINE TUMORS.
Amit Tirosh, J. Keith Killian, Yuelin Jack Zhu, David Petersen, Jennifer Walling, Ronit Mor-Cohen, Vladimir Neychev, Holly Stevenson, Xavier M. Keutgen, Dhaval Patel, Naris Nilubol, Paul Meltzer, and Electron Kebebew. Endocr Pract. 2019 Mar 13.
Markers of MEK inhibitor resistance in low-grade serous ovarian cancer: EGFR is a potential therapeutic target.
Fernandez ML, Dawson A, Hoenisch J, Kim H, Bamford S, Salamanca C, DiMattia G, Shepherd T, Cremona M, Hennessy B, Anderson S, Volik S, Collins CC, Huntsman DG, Carey MS. Cancer Cell Int. 2019 Jan 8;19:10.
Low-pass Whole-genome Sequencing of Circulating Cell-free DNA Demonstrates Dynamic Changes in Genomic Copy Number in a Squamous Lung Cancer Clinical Cohort.
Chen X, Chang CW, Spoerke JM, Yoh KE, Kapoor V, Baudo C, Aimi J, Yu M, Liang-Chu MMY, Suttmann R, Huw LY, Gendreau S, Cummings C, Lackner MR. Clin Cancer Res. 2019 Apr 1;25(7):2254-2263.
Learn more about BioDiscovery’s CNV from NGS algorithm! View this webinar recording to see how BAM MSR performs across different types of data.
