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Intersect-then-combine approach: improving the performance of somatic variant calling in whole exome sequencing data using multiple aligners and callers.
Callari, Maurizio; Sammut, Stephen-John; De Mattos-Arruda, Leticia; Bruna, Alejandra; Rueda, Oscar M; Chin, Suet-Feung; Caldas, Carlos.
Affiliation
  • Callari M; CRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
  • Sammut SJ; CRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
  • De Mattos-Arruda L; CRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
  • Bruna A; CRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
  • Rueda OM; CRUK Cambridge Institute, University of Cambridge, Cambridge, UK.
  • Chin SF; CRUK Cambridge Institute, University of Cambridge, Cambridge, UK. suet-feung.chin@cruk.cam.ac.uk.
  • Caldas C; CRUK Cambridge Institute, University of Cambridge, Cambridge, UK. carlos.caldas@cruk.cam.ac.uk.
Genome Med ; 9(1): 35, 2017 04 18.
Article in En | MEDLINE | ID: mdl-28420412
Bioinformatic analysis of genomic sequencing data to identify somatic mutations in cancer samples is far from achieving the required robustness and standardisation. In this study we generated a whole exome sequencing benchmark dataset using the platinum genome sample NA12878 and developed an intersect-then-combine (ITC) approach to increase the accuracy in calling single nucleotide variants (SNVs) and indels in tumour-normal pairs. We evaluated the effect of alignment, base quality recalibration, mutation caller and filtering on sensitivity and false positive rate. The ITC approach increased the sensitivity up to 17.1%, without increasing the false positive rate per megabase (FPR/Mb) and its validity was confirmed in a set of clinical samples.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome, Human / Sequence Analysis, DNA / Computational Biology / Mutation / Neoplasms Type of study: Diagnostic_studies Limits: Humans Language: En Journal: Genome Med Year: 2017 Document type: Article Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome, Human / Sequence Analysis, DNA / Computational Biology / Mutation / Neoplasms Type of study: Diagnostic_studies Limits: Humans Language: En Journal: Genome Med Year: 2017 Document type: Article Country of publication: United kingdom