Evaluating the quality of the 1000 genomes project data

Belsare, Saurabh; Levy‐Sakin, Michal; Mostovoy, Yulia; Durinck, Steffen; Chaudhuri, Subhra; Xiao, Ming; Peterson, Andrew S.; Kwok, Pui‐Yan; Seshagiri, Somasekar; Wall, Jeffrey D.

doi:10.1186/s12864-019-5957-x

Cited by 51 publications

(45 citation statements)

References 31 publications

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“…However, for genomes with very high mutation rates, such as HIV-1 [68], recurrence is sufficiently high to make estimates of allele age meaningless. In addition, while we have shown GEVA to be robust to realistic levels of sequencing and haplotype phasing error, the actual structures of error found in reference data sources, such as TGP [69], have additional complexity whose effect is unknown.…”

Section: Discussionmentioning

confidence: 98%

Dating genomic variants and shared ancestry in population-scale sequencing data

Albers

McVean

2018

Preprint

118

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The origin and fate of new mutations within species is the fundamental process underlying evolution. However, while much attention has been focused on characterizing the presence, frequency, and phenotypic impact of genetic variation, the evolutionary histories of most variants are largely unexplored. We have developed a nonparametric approach for estimating the date of origin of genetic variants in large-scale sequencing data sets. The accuracy and robustness of the approach is demonstrated through simulation. Using data from two publicly available human genomic diversity resources, we estimated the age of more than 45 million single nucleotide polymorphisms (SNPs) in the human genome and release the Atlas of Variant Age as a public online database. We characterize the relationship between variant age and frequency in different geographical regions, and demonstrate the value of age information in interpreting variants of functional and selective importance. Finally, we use allele age estimates to power a rapid approach for inferring the ancestry shared between individual genomes, to quantify genealogical relationships at different points in the past, as well as describe and explore the evolutionary history of modern human populations.

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Section: Discussionmentioning

confidence: 98%

Dating genomic variants and shared ancestry in population-scale sequencing data

Albers

McVean

2018

Preprint

118

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“…However, for genomes with very high mutation rates, such as HIV-1 [72], recurrence is sufficiently high to make estimates of allele age meaningless. In addition, while we have shown GEVA to be robust to realistic levels of sequencing and haplotype phasing error, the actual structures of error found in reference data sources, such as the TGP, have additional complexity whose effect is unknown [73].…”

Section: Discussionmentioning

confidence: 98%

Dating genomic variants and shared ancestry in population-scale sequencing data

2020

View full text Add to dashboard Cite

The origin and fate of new mutations within species is the fundamental process underlying evolution. However, while much attention has been focused on characterizing the presence, frequency, and phenotypic impact of genetic variation, the evolutionary histories of most variants are largely unexplored. We have developed a nonparametric approach for estimating the date of origin of genetic variants in large-scale sequencing data sets. The accuracy and robustness of the approach is demonstrated through simulation. Using data from two publicly available human genomic diversity resources, we estimated the age of more than 45 million single-nucleotide polymorphisms (SNPs) in the human genome and release the Atlas of Variant Age as a public online database. We characterize the relationship between variant age and frequency in different geographical regions and demonstrate the value of age information in interpreting variants of functional and selective importance. Finally, we use allele age estimates to power a rapid approach for inferring the ancestry shared between individual genomes and to quantify genealogical relationships at different points in the past, as well as to describe and explore the evolutionary history of modern human populations.

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“…It was also not surprising to find that the variant allele frequency for c.833T>C was underestimated when it occurred in cis given that the 68 bp insertion, which also includes the c.833T wild-type base, is almost identical in sequence to the reference genome. Phasing and imputation errors of rare variants in the 1000 Genomes data have been attributed to the limited sample size 35 . Our findings suggest, though, that the c.[833T>C;844_845ins68] complex variant may have remained undetected in the 1000 Genomes samples as a result of the alignment and variant calling methods used in the original NGS analysis, and that there may be other complex or rare variants in these data that also have gone underreported.…”

Section: Discussionmentioning

confidence: 99%

A customized scaffolds approach for the detection and phasing of complex variants by next-generation sequencing

Zeng

Leach

Zhou

et al. 2020

Sci Rep

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Next-generation sequencing (NGS) is widely used in genetic testing for the highly sensitive detection of single nucleotide changes and small insertions or deletions. However, detection and phasing of structural variants, especially in repetitive or homologous regions, can be problematic due to uneven read coverage or genome reference bias, resulting in false calls. To circumvent this challenge, a computational approach utilizing customized scaffolds as supplementary reference sequences for read alignment was developed, and its effectiveness demonstrated with two CBS gene variants: NM_000071.2:c.833T>C and NM_000071.2:c.[833T>C; 844_845ins68]. Variant c.833T>C is a known causative mutation for homocystinuria, but is not pathogenic when in cis with the insertion, c.844_845ins68, because of alternative splicing. Using simulated reads, the custom scaffolds method resolved all possible combinations with 100% accuracy and, based on > 60,000 clinical specimens, exceeded the performance of current approaches that only align reads to GRCh37/hg19 for the detection of c.833T>C alone or in cis with c.844_845ins68. Furthermore, analysis of two 1000 Genomes Project trios revealed that the c.[833T>C; 844_845ins68] complex variant had previously been undetected in these datasets, likely due to the alignment method used. This approach can be configured for existing workflows to detect other challenging and potentially underrepresented variants, thereby augmenting accurate variant calling in clinical NGS testing.

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Evaluating the quality of the 1000 genomes project data

Cited by 51 publications

References 31 publications

Dating genomic variants and shared ancestry in population-scale sequencing data

Dating genomic variants and shared ancestry in population-scale sequencing data

Dating genomic variants and shared ancestry in population-scale sequencing data

A customized scaffolds approach for the detection and phasing of complex variants by next-generation sequencing

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