Truvari: Refined Structural Variant Comparison Preserves Allelic Diversity

English, Adam C.; Menon, Vipin; Gibbs, Richard A.; Metcalf, Ginger; Sedlazeck, Fritz J.

doi:10.1101/2022.02.21.481353

Cited by 29 publications

(36 citation statements)

References 40 publications

(48 reference statements)

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“…Using the same PacBio-HiFi dataset, we called structural variants (SVs) using Sniffles2 36 and analyzed the results using truvari 37 (Section 4.5.2). We evaluated the SV calls using the GIAB Tier 1 benchmark regions for GRCh37 28 and the GIAB CMRG benchmark for GRCh38 26 .…”

Section: Resultsmentioning

confidence: 99%

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Improved sequence mapping using a complete reference genome and lift-over

Chen

Paulin

Sedlazeck

et al. 2022

Preprint

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Complete, telomere-to-telomere genome assemblies promise improved analyses and the discovery of new variants, but many essential genomic resources remain associated with older reference genomes. Thus, there is a need to translate genomic features and read alignments between references. Here we describe a new method called levioSAM2 that accounts for reference changes and performs fast and accurate lift-over between assemblies using a whole-genome map. In addition to enabling the use of multiple references, we demonstrate that aligning reads to a high-quality reference (e.g. T2T-CHM13) and lifting to an older reference (e.g. GRCh38) actually improves the accuracy of the resulting variant calls on the old reference. By leveraging the quality improvements of T2T-CHM13, levioSAM2 reduces small-variant calling errors by 11.4-39.5% compared to GRC-based mapping using real Illumina datasets. LevioSAM2 also improves long-read-based structural variant calling and reduces errors from 3.8-11.8% for a PacBio HiFi dataset. Performance is especially improved for a set of complex medically-relevant genes, where the GRC references are lower quality. The software is available at https://github.com/milkschen/leviosam2 under the MIT license.

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Section: Resultsmentioning

confidence: 99%

“…We next compressed the VCF files for each dataset using bgzip and indexed them with tabix 49 . Finally, we benchmarked and compared the SV calls using the GIAB Tier 1 benchmark regions for GRCh37 28 and the GIAB CMRG benchmark for GRCh38 26 using truvari 2.1 37 and following the GIAB benchmarking instructions.…”

Section: Methodsmentioning

confidence: 99%

Improved sequence mapping using a complete reference genome and lift-over

Chen

Paulin

Sedlazeck

et al. 2022

Preprint

Self Cite

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“…Recall and precision were calculated within the refined Dipcall confident regions (Methods) and then stratified by the GIAB v3.0 genomic context. To evaluate the SV (!50 bp) calling performance, the autosomal SVs from a given pangenome graph (query set) were compared to the consensus SV call set (truth set) for each individual using truvari bench (v3.2.0, (English et al, 2022)) with options --multimatch -r 1000 -C 1000 -O 0.0 -p 0.0 -P 0.3 -s 50 -S 15 --sizemax 100000 --includebed <Dipcall confident regions>. Recall and precision were then stratified by the GIAB v3 genomic context and by variant length.…”

Section: Benchmarking Variantsmentioning

confidence: 99%

A Draft Human Pangenome Reference

Liao

Asri

Ebler

et al. 2022

Preprint

118

226

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The Human Pangenome Reference Consortium (HPRC) presents a first draft human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals. These assemblies cover more than 99% of the expected sequence and are more than 99% accurate at the structural and base-pair levels. Based on alignments of the assemblies, we generated a draft pangenome that captures known variants and haplotypes, reveals novel alleles at structurally complex loci, and adds 119 million base pairs of euchromatic polymorphic sequence and 1,529 gene duplications relative to the existing reference, GRCh38. Roughly 90 million of the additional base pairs derive from structural variation. Using our draft pangenome to analyze short-read data reduces errors when discovering small variants by 34% and boosts the detected structural variants per haplotype by 104% compared to GRCh38-based workflows, and by 34% compared to using previous diversity sets of genome assemblies.

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“…We assessed the performance of Sniffles2 with respect to Sniffles 27 (v1.12), cuteSV 45 (v1.0.11), PBSV 46 (v2.6.2) and SVIM 47 (v1.4.2) using Truvari 48 and the GIAB recommended parameters 49 . Figure2 shows the results across different GIAB benchmarks.…”

Section: Resultsmentioning

confidence: 99%

“…We used Truvari 48 (version 2.1) for benchmarking the accuracy of all SV callers across datasets. For benchmarking, we used the -- passonly parameter to include only those SVs from caller and gold standard that are not marked as filtered.…”

Section: Methodsmentioning

confidence: 99%

Comprehensive Structural Variant Detection: From Mosaic to Population-Level

Smolka

Paulin

Grochowski

et al. 2022

Preprint

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Long-read Structural Variation (SV) calling remains a challenging but highly accurate way to identify complex genomic rearrangements. Here, we present Sniffles2, which is faster and more accurate than state-of-the-art SV caller across different coverages, sequencing technologies, and SV types. Furthermore, Sniffles2 solves the problem of family to population-level SV calling to produce fully genotyped VCF files by introducing a gVCF file concept. Across 31 Mendelian samples, we accurately identified causative SVs around MECP2, including highly complex alleles with three overlapping SVs. Sniffles2 also enables the detection of mosaic SVs in bulk long-read data. This way, we were able to identify multiple mosaic SVs across a multiple system atrophy patient brain. The identified SV showed a remarkable diversity within the cingulate cortex, impacting both genes involved in neuron function and repetitive elements. In summary, we demonstrate the utility and versatility of Sniffles2 to identify SVs from the mosaic to population levels.

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Truvari: Refined Structural Variant Comparison Preserves Allelic Diversity

Cited by 29 publications

References 40 publications

Improved sequence mapping using a complete reference genome and lift-over

Improved sequence mapping using a complete reference genome and lift-over

A Draft Human Pangenome Reference

Comprehensive Structural Variant Detection: From Mosaic to Population-Level

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