VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data

Müller, Heiko; Heredia, Raúl Jimenez; Krolo, Ana; Hirschmugl, Tatjana; Dmytrus, Jasmin; Boztuğ, Kaan; Bock, Christoph

doi:10.1093/nar/gkx425

Cited by 35 publications

(32 citation statements)

References 31 publications

(35 reference statements)

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“…6 Pik3cg -/mice display reduced NK-cell numbers, defective NK-cell development and consequently, decreased cytotoxicity. 3 We also observed reduced frequency, absolute counts and degranulation of patient NK cells compared to cells derived from the mother and HD (Table 1, Fig. S1B-C).…”

mentioning

confidence: 58%

“…Genomes, gnomAD, and dbSNP build 149. After further filtering steps for nonsense, missense, and splice-site variants using VCF.Filter software, 3 an internal database was used to filter for recurrent variants. Moreover, variants were prioritized using tools, such as SIFT, Polyphen-2 and the combined annotation dependent depletion (CADD) score, 4,5 that predict the deleteriousness of a present variant.…”

Section: Whole Exome Sequencing and Analysismentioning

confidence: 99%

“…Studies on PI3K in human disease have highlighted PI3K-gamma (PI3Kγ) as an appealing drug target for treatment of human disorders. 2 Murine PI3Kγ studies showed its importance in regulating innate immune functions and development [3][4] and activation of T cells, 5 revealing its role in controlling inflammation. 4 However, its role in the human immune system and diseases remains to be investigated.…”

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confidence: 99%

“…The impaired NK cell compartment may have contributed to the observed clinical HLH-like phenotype. 3 We further hypothesized that a defect in PI3Kγ signaling would affect TCR-driven activation of T cells. 7 Patient T-cell subsets were comparable to HD (Table S2).…”

mentioning

confidence: 99%

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Germline biallelic PIK3CG mutations in a multifaceted immunodeficiency with immune dysregulation

Thian¹,

Hoeger²,

Kamnev³

et al. 2020

haematol

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mentioning

confidence: 58%

Section: Whole Exome Sequencing and Analysismentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Germline biallelic PIK3CG mutations in a multifaceted immunodeficiency with immune dysregulation

Thian¹,

Hoeger²,

Kamnev³

et al. 2020

haematol

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“…Experienced researchers might prefer to keep their in-house annotations for downstream analysis. Other tools including VCF-Miner (Hart et al, 2016), VCF.Filter (Muller et al, 2017), myVCF (Pietrelli & Valenti, 2017), and BrowseVCF (Salatino & Ramraj, 2017) skip the annotation step and allow users to filter variants with their in-house annotations in the VCF. However, in most cases, they require users to annotate the VCF with other annotation tools before querying and filtering variants.…”

Section: Introductionmentioning

confidence: 99%

VCF‐Server: A web‐based visualization tool for high‐throughput variant data mining and management

Jiang

Zhao

et al. 2019

Molec Gen & Gen Med

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Background Next‐generation sequencing (NGS) has been widely used in both clinics and research. It has become the most powerful tool for diagnosing genetic disorders and investigating disease etiology through the discovery of genetic variants. Variants identified by NGS are stored in variant call format (VCF) files. However, querying and filtering VCF files are extremely difficult for researchers without programming skills. Furthermore, as the mutation data are increasing exponentially, there is an urgent need to develop tools to manage these variant data in a centralized way. Methods The VCF‐Server was developed as a web‐based visualization tool to support the interactive analysis of genetic variant data. It allows researchers and medical geneticists to manage, annotate, filter, query, and export variants in a fast and effective way. Results In this study, we developed the VCF‐Server, a powerful and easily accessible tool for researchers and medical geneticists to perform variant analysis. Users can query VCFs, annotate, and filter variants without knowing programming code. Once the VCF file is uploaded, VCF‐Server allows users to annotate the VCF with commonly used databases or user‐defined variant annotations (including variant blacklist and whitelist). Variant information in the VCF is shown visually via the interactive graphical interface. Users can filter the variants with flexible filtering rules, and the prioritized variants can be exported locally for further analysis. As VCF‐Server adopts a web file system, files in the VCF‐Server can be stored and managed in a centralized way. Moreover, VCF‐Server allows direct web‐based analysis (accessible through either desktop computers or mobile devices) as well as local deployment. Conclusions With an easy‐to‐use graphical interface, VCF‐Server allows researchers with little bioinformatics background to explore and mine mutation data, which may broaden the application of NGS technology in clinics and research. The tool is freely available for use at https://www.diseasegps.org/VCF-Server?lan = eng .

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Mind the gap: resources required to receive, process and interpret research-returned whole genome data

2019

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Most genotype-phenotype studies have historically lacked population diversity, impacting the generalizability of findings and thereby limiting the ability to equitably implement precision medicine. This well-documented problem has generated much interest in ascertainment of new cohorts with an emphasis on multiple dimensions of diversity, including race/ethnicity, gender, age, socioeconomic status, disability, and geography. The most well-known of these new cohort efforts is arguably All of Us, formerly known as the Precision Medicine Cohort Initiative Program. All of Us intends to ascertain at least one million participants in the United States representative of the multiple dimensions of diversity. As an incentive to participate, All of Us is offering the return of research results, including whole genome sequencing data, as well as the opportunity to contribute to the scientific process as non-scientists. The scale and scope of the proposed return of research results are unprecedented. Here, we briefly review possible return of genetic data models, including the likely data file formats and modes of data transfer or access. We also review the resources required to access and interpret the genetic or genomic data once received by the average participant, highlighting the nuanced anticipated barriers that will challenge both the digitally, computationally literate and illiterate participant alike. This inventory of resources required to receive, process, and interpret return of research results exposes the potential for access Terms of use and reuse: academic research for non-commercial purposes, see here for full terms. https://www.springer.com/aamterms-v1

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VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data

Cited by 35 publications

References 31 publications

Germline biallelic PIK3CG mutations in a multifaceted immunodeficiency with immune dysregulation

Germline biallelic PIK3CG mutations in a multifaceted immunodeficiency with immune dysregulation

VCF‐Server: A web‐based visualization tool for high‐throughput variant data mining and management

Mind the gap: resources required to receive, process and interpret research-returned whole genome data

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