VariantDB: a flexible annotation and filtering portal for next generation sequencing data

Vandeweyer, Geert; Laer, Lut Van; Loeys, Bart; Bulcke, Tim Van den; Kooy, R. Frank

doi:10.1186/s13073-014-0074-6

Cited by 63 publications

(35 citation statements)

References 55 publications

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“…An in-house annotation and filtering tool VariantDB [59] (available online: http://www.biomina.be/app/variantdb/) was used to identify Single Nucleotide Variants (SNV). The NM_000245.2 sequence was used for c-Met, while NM_000546.5 was used for TP53 sequences.…”

Section: Discussionmentioning

confidence: 99%

The Role of c-Met as a Biomarker and Player in Innate and Acquired Resistance in Non-Small-Cell Lung Cancer: Two New Mutations Warrant Further Studies

et al. 2019

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The c-Met receptor is a therapeutically actionable target in non-small-cell lung cancer (NSCLC), with one approved drug and several agents in development. Most suitable biomarkers for patient selection include c-Met amplification and exon-14 skipping. Our retrospective study focused on the frequency of different c-Met aberrations (overexpression, amplification and mutations) in 153 primary, therapy-naïve resection samples and their paired metastases, from Biobank@UZA. Furthermore, we determined the correlation of c-Met expression with clinicopathological factors, Epidermal Growth Factor Receptor (EGFR)-status and TP53 mutations. Our results showed that c-Met expression levels in primary tumors were comparable to their respective metastases. Five different mutations were detected by deep sequencing: three (E168D, S203T, N375S) previously described and two never reported (I333T, G783E). I333T, a new mutation in the Sema(phorin) domain of c-Met, might influence the binding of antibodies targeting the HGF-binding domain, potentially causing innate resistance. E168D and S203T mutations showed a trend towards a correlation with high c-Met expression (p = 0.058). We found a significant correlation between c-MET expression, EGFR expression (p = 0.010) and EGFR mutations (p = 0.013), as well as a trend (p = 0.057) with regards to TP53 mutant activity. In conclusion this study demonstrated a strong correlation between EGFR mutations, TP53 and c-Met expression in therapy-naïve primary resection samples. Moreover, we found two new c-Met mutations that warrant further studies.

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Section: Discussionmentioning

confidence: 99%

The Role of c-Met as a Biomarker and Player in Innate and Acquired Resistance in Non-Small-Cell Lung Cancer: Two New Mutations Warrant Further Studies

et al. 2019

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“…Samples were paired-end sequenced using 2x100 bp on a HiSeq1500 in high output mode (Illumina, San Diego, CA). Enrichment, data analysis, variant annotation and confirmation of the variants were performed as previously described 10,11. GRCh37 was used as a reference build.…”

Section: Methodsmentioning

confidence: 99%

Loss-of-function mutations in the X-linked biglycan gene cause a severe syndromic form of thoracic aortic aneurysms and dissections

Meester

Vandeweyer

Pintelon

et al. 2017

Genetics in Medicine

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102

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Purpose Thoracic aortic aneurysm and dissection (TAAD) is typically inherited in an autosomal dominant manner, but rare X-linked families have been described. So far the only known X-linked gene is FLNA, which is associated with the periventricular nodular heterotopia type of Ehlers-Danlos syndrome. However, mutations in this gene only explain a small number of X-linked TAAD families. Methods We performed targeted resequencing of 368 candidate genes in a cohort of 11 molecularly unexplained Marfan probands. Subsequently, Sanger sequencing of BGN in 360 male and 155 female molecularly unexplained TAAD probands was carried out. Results We found five individuals with loss-of-function mutations in BGN, encoding the small leucine-rich proteoglycan biglycan. The clinical phenotype is characterized by early onset aortic aneurysm and dissection. Other recurrent findings include hypertelorism, pectus deformity, joint hypermobility, contractures and mild skeletal dysplasia. Fluorescent stainings revealed an increase in TGF-β signalling, evidenced by an increase in nuclear pSMAD2 in aortic wall. Our results are in line with prior reports demonstrating that Bgn-deficient male BALB/cA mice die from aortic rupture. Conclusion In conclusion, BGN gene defects in humans cause an X-linked syndromic form of severe TAAD, associated with preservation of elastic fibres and increased TGF-β signalling.

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“…However, since the main focus of these tools is variant calling, their output is typically presented as basic lists of detected variants, which have to be further inspected and annotated to yield applicable information. Annotation tools like VariantDB [18] or VIS [19] start from a list of detected variants and can accumulate and manage annotation information from various sources, but are limited to basic research contexts. Neither of these tools addresses specific clinical requirements like reproducibility, long-term data storage or usability for non-bioinformaticians, and are therefore of limited use in a clinical setting.…”

Section: Related Workmentioning

confidence: 99%

AMLVaran: a software approach to implement variant analysis of targeted NGS sequencing data in an oncological care setting

et al. 2020

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Background: Next-Generation Sequencing (NGS) enables large-scale and cost-effective sequencing of genetic samples in order to detect genetic variants. After successful use in research-oriented projects, NGS is now entering clinical practice. Consequently, variant analysis is increasingly important to facilitate a better understanding of disease entities and prognoses. Furthermore, variant calling allows to adapt and optimize specific treatments of individual patients, and thus is an integral part of personalized medicine. However, the analysis of NGS data typically requires a number of complex bioinformatics processing steps. A flexible and reliable software that combines the variant analysis process with a simple, user-friendly interface is therefore highly desirable, but still lacking. Results: With AMLVaran (AML Variant Analyzer), we present a web-based software, that covers the complete variant analysis workflow of targeted NGS samples. The software provides a generic pipeline that allows free choice of variant calling tools and a flexible language (SSDL) for filtering variant lists. AMLVaran's interactive website presents comprehensive annotation data and includes curated information on relevant hotspot regions and driver mutations. A concise clinical report with rule-based diagnostic recommendations is generated. An AMLVaran configuration with eight variant calling tools and a complex scoring scheme, based on the somatic variant calling pipeline appreci8, was used to analyze three datasets from AML and MDS studies with 402 samples in total. Maximum sensitivity and positive predictive values were 1.0 and 0.96, respectively. The tool's usability was found to be satisfactory by medical professionals. Conclusion: Coverage analysis, reproducible variant filtering and software usability are important for clinical assessment of variants. AMLVaran performs reliable NGS variant analyses and generates reports fulfilling the requirements of a clinical setting. Due to its generic design, the software can easily be adapted for use with different targeted panels for other tumor entities, or even for whole-exome data. AMLVaran has been deployed to a public web server and is distributed with Docker scripts for local use.

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VariantDB: a flexible annotation and filtering portal for next generation sequencing data

Cited by 63 publications

References 55 publications

The Role of c-Met as a Biomarker and Player in Innate and Acquired Resistance in Non-Small-Cell Lung Cancer: Two New Mutations Warrant Further Studies

The Role of c-Met as a Biomarker and Player in Innate and Acquired Resistance in Non-Small-Cell Lung Cancer: Two New Mutations Warrant Further Studies

Loss-of-function mutations in the X-linked biglycan gene cause a severe syndromic form of thoracic aortic aneurysms and dissections

AMLVaran: a software approach to implement variant analysis of targeted NGS sequencing data in an oncological care setting

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