Accurate, scalable cohort variant calls using DeepVariant and GLnexus

Yun, Taedong; Li, Hai; Chang, Pi-Chuan; Lin, Michael; Carroll, Andrew; McLean, Cory Y.

doi:10.1093/bioinformatics/btaa1081

Cited by 148 publications

(133 citation statements)

References 49 publications

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“…To assess the computational efficiency of DeepTrio compared to other methods of generating trio calls, we ran pipelines on the Illumina 35x WGS samples using the same hardware: a 16-CPU thread machine (n1-standard-16) available on Google Cloud Platform. This was chosen as representative of typical runs, though there are faster (and more expensive) or slower (but cheaper) methods to run these pipelines (an analysis of single-machine scaling can be found in the DeepVariant-GLnexus paper 38 ).…”

Section: Computational Efficiency Of Deeptrio and Other Trio-calling Pipelinesmentioning

confidence: 99%

DeepTrio: Variant Calling in Families Using Deep Learning

Kolesnikov

Goel

Nattestad

et al. 2021

Preprint

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Every human inherits one copy of the genome from their mother and another from their father. Parental inheritance helps us understand the transmission of traits and genetic diseases, which often involve de novo variants and rare recessive alleles. Here we present DeepTrio, which learns to analyze child-mother-father trios from the joint sequence information, without explicit encoding of inheritance priors. DeepTrio learns how to weigh sequencing error, mapping error, and de novo rates and genome context directly from the sequence data. DeepTrio has higher accuracy on both Illumina and PacBio HiFi data when compared to DeepVariant. Improvements are especially pronounced at lower coverages (with 20x DeepTrio roughly equivalent to 30x DeepVariant). As DeepTrio learns directly from data, we also demonstrate extensions to exome calling solely by changing the training data. DeepTrio includes pre-trained models for Illumina WGS, Illumina exome, and PacBio HiFi.

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Section: Computational Efficiency Of Deeptrio and Other Trio-calling Pipelinesmentioning

confidence: 99%

DeepTrio: Variant Calling in Families Using Deep Learning

Kolesnikov

Goel

Nattestad

et al. 2021

Preprint

Self Cite

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“…SNPs and small indels) for each sample. GLNexus 44 was then used to conduct a joint analysis of variants across all six samples. Over 12 million unique variants were identified before filtering.…”

Section: Resultsmentioning

confidence: 99%

Whole genome sequencing of nearly isogenic WMI and WLI inbred rats identifies genes potentially involved in depression and stress reactivity

Jong

Kim

Guryev

et al. 2021

Sci Rep

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The WMI and WLI inbred rats were generated from the stress-prone, and not yet fully inbred, Wistar Kyoto (WKY) strain. These were selected using bi-directional selection for immobility in the forced swim test and were then sib-mated for over 38 generations. Despite the low level of genetic diversity among WKY progenitors, the WMI substrain is significantly more vulnerable to stress relative to the counter-selected WLI strain. Here we quantify numbers and classes of genomic sequence variants distinguishing these substrains with the long term goal of uncovering functional and behavioral polymorphism that modulate sensitivity to stress and depression-like phenotypes. DNA from WLI and WMI was sequenced using Illumina xTen, IonTorrent, and 10X Chromium linked-read platforms to obtain a combined coverage of ~ 100X for each strain. We identified 4,296 high quality homozygous SNPs and indels between the WMI and WLI. We detected high impact variants in genes previously implicated in depression (e.g. Gnat2), depression-like behavior (e.g. Prlr, Nlrp1a), other psychiatric disease (e.g. Pou6f2, Kdm5a, Reep3, Wdfy3), and responses to psychological stressors (e.g. Pigr). High coverage sequencing data confirm that the two substrains are nearly coisogenic. Nonetheless, the small number of sequence variants contributes to numerous well characterized differences including depression-like behavior, stress reactivity, and addiction related phenotypes. These selected substrains are an ideal resource for forward and reverse genetic studies using a reduced complexity cross.

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“…From aligned data, DeepVariant [ 50 ] (version 0.9.0) was used to call the variants to make vcf files [ 51 ]. Vcf files were merged using GLnexus [ 52 ] (version 1.2.6) (—config DeepVariantWGS). To process and analyze vcf files, bcftools [ 43 ] (version 1.9), bgzip implemented in tabix [ 43 ] (version 0.2.5), vcffilter implemented in vcflib [ 53 ] (version 1.0.0_rc3), and “grep” and “awk” commands of Linux were used.…”

Section: Methodsmentioning

confidence: 99%

Genomic diversity of 39 samples of Pyropia species grown in Japan

et al. 2021

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Some Pyropia species, such as nori (P. yezoensis), are important marine crops. We conducted a phylogenetic analysis of 39 samples of Pyropia species grown in Japan using organellar genome sequences. A comparison of the chloroplast DNA sequences with those from China showed a clear genetic separation between Japanese and Chinese P. yezoensis. Conversely, comparing the mitochondrial DNA sequences did not separate Japanese and Chinese P. yezoensis. Analysis of organellar genomes showed that the genetic diversity of Japanese P. yezoensis used in this study is lower than that of Chinese wild P. yezoensis. To analyze the genetic relationships between samples of Japanese Pyropia, we used whole-genome resequencing to analyze their nuclear genomes. In the offspring resulting from cross-breeding between P. yezoensis and P. tenera, nearly 90% of the genotypes analyzed by mapping were explained by the presence of different chromosomes originating from two different parental species. Although the genetic diversity of Japanese P. yezoensis is low, analysis of nuclear genomes genetically separated each sample. Samples isolated from the sea were often genetically similar to those being farmed. Study of genetic heterogeneity of samples within a single aquaculture strain of P. yezoensis showed that samples were divided into two groups and the samples with frequent abnormal budding formed a single, genetically similar group. The results of this study will be useful for breeding and the conservation of Pyropia species.

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Accurate, scalable cohort variant calls using DeepVariant and GLnexus

Cited by 148 publications

References 49 publications

DeepTrio: Variant Calling in Families Using Deep Learning

DeepTrio: Variant Calling in Families Using Deep Learning

Whole genome sequencing of nearly isogenic WMI and WLI inbred rats identifies genes potentially involved in depression and stress reactivity

Genomic diversity of 39 samples of Pyropia species grown in Japan

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