A database of simulated tumor genomes towards accurate detection of somatic small variants in cancer

PloS One
Jing Meng, Yi-Ping Phoebe Chen

Abstract

Somatic mutations promote the transformation of normal cells to cancer. Accurate identification of such mutations facilitates cancer diagnosis and treatment, but biological and technological noises, including intra-tumor heterogeneity, sample contamination, uncertainties in base sequencing and read alignment, pose a big challenge to somatic mutation discovery. A number of callers have been developed to predict them from paired tumor/normal or unpaired tumor sequencing data. However, the small size of currently available experimentally validated somatic sites limits evaluation and then improvement of callers. Fortunately, NIST reference material NA12878 genome has been well-characterized with publicly available high-confidence genotype calls, and biological and technological noises can be computationally generalized to the number of sub-clones, the VAFs, the sequencing and mapping qualities. We used BAMSurgeon to create simulated tumors by introducing somatic small variants (SNVs and small indels) into homozygous reference or wildtype sites of NA12878. We generated 135 simulated tumors from 5 pre-tumors/normals. These simulated tumors vary in sequencing and subsequent mapping error profiles, read length, the number of sub-clones...Continue Reading

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Citations

Feb 12, 2020·Archives of Pathology & Laboratory Medicine·Jeffrey A SoRelleBrandi L Cantarel
Feb 9, 2020·Genome Biology·David LähnemannAlexander Schönhuth
May 1, 2021·Cancers·Lau K VestergaardEstrid V Høgdall
Jun 7, 2021·BMC Bioinformatics·Yunfeng WangDaniel Gautheret

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Datasets Mentioned

BETA
NA12878

Methods Mentioned

BETA
PCR

Software Mentioned

BAMSurgeon DREAM
Lancet
PG
Strelka2
Platinum Genomes PG
. py
RepeatMasker
BEDtools merge
py
DeepVariant

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