TransVar: a multilevel variant annotator for precision genomics

Zhou, Wanding; Chen, Tenghui; Chong, Zechen; Rohrdanz, Mary A.; Melott, James M.; Wakefield, Chris; Zeng, Jia; Weinstein, John N.; Meric‐Bernstam, Funda; Mills, Gordon B.; Chen, Ken

doi:10.1038/nmeth.3622

Cited by 67 publications

(58 citation statements)

References 6 publications

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“…We excluded genes that were not covered in the earlier gene lists. Genomic position was inferred from protein change using TransVar (http://bioinformatics.mdanderson.org/transvarweb) [55]. …”

Section: Methodsmentioning

confidence: 99%

Genomic landscape of high-grade meningiomas

et al. 2017

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High-grade meningiomas frequently recur and are associated with high rates of morbidity and mortality. To determine the factors that promote the development and evolution of these tumors, we analyzed the genomes of 134 high-grade meningiomas and compared this information with data from 595 previously published meningiomas. High-grade meningiomas had a higher mutation burden than low-grade meningiomas but did not harbor any significantly mutated genes aside from NF2. High-grade meningiomas also possessed significantly elevated rates of chromosomal gains and losses, especially among tumors with monosomy 22. Meningiomas previously treated with adjuvant radiation had significantly more copy number alterations than radiation-induced or radiation-naïve meningiomas. Across serial recurrences, genomic disruption preceded the emergence of nearly all mutations, remained largely uniform across time, and when present in low-grade meningiomas correlated with subsequent progression to a higher grade. In contrast to the largely stable copy number alterations, mutations were strikingly heterogeneous across tumor recurrences, likely due to extensive geographic heterogeneity in the primary tumor. While high-grade meningiomas harbored significantly fewer overtly targetable alterations than low-grade meningiomas, they contained numerous mutations that are predicted to be neoantigens, suggesting that immunologic targeting may be of therapeutic value.

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Section: Methodsmentioning

confidence: 99%

Genomic landscape of high-grade meningiomas

et al. 2017

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“…The programmed script for the database displays the variants. The annotation was performed using relatively accepted public programs including TransVar for the coordinate conversion [18], vcfanno for the table annotation [8], Variant Effect Predictor to convert the g.HGVS format to the VCF format [16], CrossMap for the lift-over between hg10 and GRCh38 [17], and InterVar for the semi-automatic variant scoring [5].…”

Section: Methodsmentioning

confidence: 99%

“…Positional information on the variants at the cDNA sequence or protein sequence levels were converted to genome coordinates (GRCh37 or GRCh38) using TransVar software [18]. Once the genome coordinates were determined by the curators, the variant information per the genome coordinate was again converted to the cDNA sequence or protein sequence level to ensure that the entire conversion process was performed in an appropriate manner.…”

Section: Methodsmentioning

confidence: 99%

Japanese pathogenic variant database: DPV

Suzuki

Kurosawa

Fukuda

et al. 2018

TRD

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Abstract. Databases of pathogenic variants form the basis for clinical genomic diagnosis using next-generation sequencers. ClinVar and the Human Gene Mutation Database (HGMD) are two major databases for pathogenic variants. However, ethnic diversity in the distributions of pathogenic variants in these databases has been observed; thus, geographic region-specific variant databases are required. We established a Japanese pathogenic variant database in 2016 and began registering pathogenic variants from published articles written by Japanese researchers. The criteria for registration are as follows: 1) the variant has been validated using Sanger sequencing, 2) the minor allele frequency of the variant is lower than 0.03 in the normal Japanese population, and 3) the clinical features of the patient have been critically evaluated by multiple clinicians and geneticists. All registered variants can be downloaded as an aggregated single VCF file to use in laboratories. We are presently curating variants from more than 2000 articles and estimate the registration of >10,000 pathogenic variants derived from the Japanese population. Although the number of registered variants remains relatively small, the clinical genetics community in Japan has begun to work on this initiative in a concerted manner.

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“…These steps are described in the import document and may include conversion of nongenomic to genomic variant coordinates using TransVar (Zhou et al, 2015), biocommons UTA and HGVS packages (Hart et al, 2015), UCSC liftOver of genomic coordinates to GRCh37/hg19 human genome assembly, conversion from zero-based to one-based 6 indexing system, correction of erroneous reference bases and so on. Once the genomic coordinates have been resolved and the uniform formatting has been applied, we use ANNOVAR (Wang et al, 2010) to annotate variants.…”

Section: Construction and Contentmentioning

confidence: 99%

VariCarta: a comprehensive database of harmonized genomic variants found in ASD sequencing studies

Belmadani

Jacobson

Holmes

et al. 2019

Preprint

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BackgroundRecent years has seen a boom in the application of the next-generation sequencing technology to the study of human diseases, including Autism Spectrum Disorder (ASD),where the focus has been on identifying rare, possibly causative genomic variants in ASD individuals. Because of the high genetic heterogeneity of ASD, a large number of subjects is needed to establish evidence for a variant or gene ASD-association, thus aggregating data across cohorts and studies is necessary. However, methodological inconsistencies and subject overlap across studies complicate data aggregation. DescriptionHere we present VariCarta, a web-based database developed to address these challenges by collecting, reconciling and consistently cataloguing literature-derived genomic variants found in ASD subjects using ongoing semi-manual curation. The careful manual curation combined with a robust data import pipeline rectifies errors, converts variants into a standardized format, identifies and harmonizes cohort overlaps and documents data provenance. The harmonization aspect is especially important since it prevents the potential double-counting of variants which can lead to inflation of gene-based evidence for ASD-association. ConclusionVariCarta is the largest collection of systematically curated, harmonized and comprehensively annotated literature-derived ASD-associated variants. The database currently contains 35,615 variant events from 8,044 subjects, collected across 50

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TransVar: a multilevel variant annotator for precision genomics

Cited by 67 publications

References 6 publications

Genomic landscape of high-grade meningiomas

Genomic landscape of high-grade meningiomas

Japanese pathogenic variant database: DPV

VariCarta: a comprehensive database of harmonized genomic variants found in ASD sequencing studies

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