Modeling performance of sample collection sites using whole exome sequencing metrics.
Autor: | Kalinava N; Bristol Myers Squibb, Princeton, NJ 08648 USA., Apfel A; Bristol Myers Squibb, Princeton, NJ 08648 USA., Cartmell R; Bristol Myers Squibb, Princeton, NJ 08648 USA., Srinivasan S; Bristol Myers Squibb, Princeton, NJ 08648 USA., Chien MS; Bristol Myers Squibb, Princeton, NJ 08648 USA., Kim KI; Bristol Myers Squibb, Princeton, NJ 08648 USA., Golhar R; Bristol Myers Squibb, Princeton, NJ 08648 USA., Bednarz KE; Bristol Myers Squibb, Princeton, NJ 08648 USA., Pant S; Bristol Myers Squibb, Princeton, NJ 08648 USA., Szustakowski J; Bristol Myers Squibb, Princeton, NJ 08648 USA., Chasalow SD; Bristol Myers Squibb, Princeton, NJ 08648 USA., Sasson A; Bristol Myers Squibb, Princeton, NJ 08648 USA., Kirov S; Bristol Myers Squibb, Princeton, NJ 08648 USA. |
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Jazyk: | angličtina |
Zdroj: | BioTechniques [Biotechniques] 2020 Dec; Vol. 69 (6), pp. 420-426. Date of Electronic Publication: 2020 Oct 26. |
DOI: | 10.2144/btn-2020-0086 |
Abstrakt: | Although next-generation sequencing assays are routinely carried out using samples from cancer trials, the sequencing data are not always of the required quality. There is a need to evaluate the performance of tissue collection sites and provide feedback about the quality of next-generation sequencing data. This study used a modeling approach based on whole exome sequencing quality control (QC) metrics to evaluate the relative performance of sites participating in the Bristol Myers Squibb Immuno-Oncology clinical trials sample collection. We identified several events for the sample swap. Overall, most sites performed well and few showed poor performance. These findings can increase awareness of sample failure and improve the quality of samples. |
Databáze: | MEDLINE |
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