Evidence map›Paper›PMID 39192052›Full record

ArticleHuman genetics2024

VCAT: an integrated variant function annotation tools.

Bi Huang, Cong Fan, Ken Chen, Jiahua Rao, Peihua Ou, Chong Tian, Yuedong Yang, David N Cooper, Huiying Zhao

Abstract read
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In one paragraph

Article in Human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Bi Huang *Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yan Jiang West Road, Guangzhou, 500001, People's Republic of China.
Cong Fan *Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yan Jiang West Road, Guangzhou, 500001, People's Republic of China.
Ken ChenSchool of Data and Computer Science, Sun Yat-Sen University, Guangzhou, People's Republic of China.
Jiahua RaoSchool of Data and Computer Science, Sun Yat-Sen University, Guangzhou, People's Republic of China.
Peihua OuSchool of Data and Computer Science, Sun Yat-Sen University, Guangzhou, People's Republic of China.
Chong TianSchool of Data and Computer Science, Sun Yat-Sen University, Guangzhou, People's Republic of China.
Yuedong YangSchool of Data and Computer Science, Sun Yat-Sen University, Guangzhou, People's Republic of China.
David N CooperSchool of Medicine, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK.
Huiying ZhaoDepartment of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yan Jiang West Road, Guangzhou, 500001, People's Republic of China. zhaohy8@mail.sysu.edu.cn.

Funding

Guangdong Key Field Research and Development Plan 2021A1515010256Guangzhou Science and Technology Research Plan 202007030010National Key Research and Development Program of China 2023YFF1204900Natural Science Foundation of China 81971190
6 · The paper itself

Abstract

The development of sequencing technology has promoted discovery of variants in the human genome. Identifying functions of these variants is important for us to link genotype to phenotype, and to diagnose diseases. However, it usually requires researchers to visit multiple databases. Here, we presented a one-stop webserver for variant function annotation tools (VCAT, https://biomed.nscc-gz.cn/zhaolab/VCAT/ ) that is the first one connecting variant to functions via the epigenome, protein, drug and RNA. VCAT is also the first one to make all annotations visualized in interactive charts or molecular structures. VCAT allows users to upload data in VCF format, and download results via a URL. Moreover, VCAT has annotated a huge number (1,262,041,068) of variants collected from dbSNP, 1000 Genomes projects, gnomAD, ICGC, TCGA, and HPRC Pangenome project. For these variants, users are able to searcher their functions, related diseases and drugs from VCAT. In summary, VCAT provides a one-stop webserver to explore the potential functions of human genomic variants including their relationship with diseases and drugs.

Indexed as

Genome, HumanMolecular Sequence AnnotationSoftwareComputational BiologyDatabases, GeneticGenetic VariationGenomicsHumans

Identifiers

PMID39192052

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.