Dataset Information

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

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, the VAF, the mutation frequency across the genome and the genomic context. Furthermore, these pure tumor/normal pairs can be mixed at desired ratios within each pair to simulate sample contamination. This database (a total size of 15 terabytes) will be of great use to benchmark somatic small variant callers and guide their improvement.

SUBMITTER: Meng J

PROVIDER: S-EPMC6116990 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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

Meng Jing J Chen Yi-Ping Phoebe YP

PloS one 20180830 8

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 si ...[more]

PMID: 30161165

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Project description:BackgroundSmall insertions and deletions (InDels) constitute the second most abundant class of genetic variants and have been found to be associated with many traits and diseases. The present study reports on the detection and characterisation of about 883 K high quality InDels from the whole-genome analysis of several modern layer chicken lines from diverse breeds.ResultsTo reduce the error rates seen in InDel detection, this study used the consensus set from two InDel-calling packages: SAMtools and Dindel, as well as stringent post-filtering criteria. By analysing sequence data from 163 chickens from 11 commercial and 5 experimental layer lines, this study detected about 883 K high quality consensus InDels with 93% validation rate and an average density of 0.78 InDels/kb over the genome. Certain chromosomes, viz, GGAZ, 16, 22 and 25 showed very low densities of InDels whereas the highest rate was observed on GGA6. In spite of the higher recombination rates on microchromosomes, the InDel density on these chromosomes was generally lower relative to macrochromosomes possibly due to their higher gene density. About 43-87% of the InDels were found to be fixed within each line. The majority of detected InDels (86%) were 1-5 bases and about 63% were non-repetitive in nature while the rest were tandem repeats of various motif types. Functional annotation identified 613 frameshift, 465 non-frameshift and 10 stop-gain/loss InDels. Apart from the frameshift and stopgain/loss InDels that are expected to affect the translation of protein sequences and their biological activity, 33% of the non-frameshift were predicted as evolutionary intolerant with potential impact on protein functions. Moreover, about 2.5% of the InDels coincided with the most-conserved elements previously mapped on the chicken genome and are likely to define functional elements. InDels potentially affecting protein function were found to be enriched for certain gene-classes e.g. those associated with cell proliferation, chromosome and Golgi organization, spermatogenesis, and muscle contraction.ConclusionsThe large catalogue of InDels presented in this study along with their associated information such as functional annotation, estimated allele frequency, etc. are expected to serve as a rich resource for application in future research and breeding in the chicken.

Dataset Information

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

Publications

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

Similar Datasets

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