ArticleHuman genetics2024
VARista: a free web platform for streamlined whole-genome variant analysis across T2T, hg38, and hg19.
Article in Human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- NSMCE2 / MMS21 structural variant causes chromosome breakage syndrome with primordial dwarfism and severe lung disease.European journal of human genetics : EJHG · 2026Article
- Xq26.2 Contiguous Gene Deletion InvolvingGenes · 2026Article
- FACS-based dual fluorescence reporter assay demonstrates efficacy of antisense oligonucleotide therapy of novelMolecular therapy. Nucleic acids · 2026Article
- A ciliopathy combining Joubert syndrome and Oro-Facial-Digital syndrome caused by bi-allelic 5'-UTR loss-of-function CEP83 variant.NPJ genomic medicine · 2025Article
- Early-Onset Movement Disorder Syndrome Caused by Biallelic Variants in PDE1B Encoding Phosphodiesterase 1B.Movement disorders : official journal of the Movement Disorder Society · 2025Article
- Unraveling MECP2 structural variants in previously elusive Rett syndrome cases through IGV interpretation.NPJ genomic medicine · 2025Article
- Importance of EQA/PT for the detection of genetic variants in comprehensive cancer genome testing.Scientific reports · 2025Article
- GeniePool 2.0: advancing variant analysis through CHM13-T2T, AlphaMissense, gnomAD V4 integration, and variant co-occurrence queries.Database : the journal of biological databases and curation · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
Abstract
With the increasing importance of genomic data in understanding genetic diseases, there is an essential need for efficient and user-friendly tools that simplify variant analysis. Although multiple tools exist, many present barriers such as steep learning curves, limited reference genome compatibility, or costs. We developed VARista, a free web-based tool, to address these challenges and provide a streamlined solution for researchers, particularly those focusing on rare monogenic diseases. VARista offers a user-centric interface that eliminates much of the technical complexity typically associated with variant analysis. The tool directly supports VCF files generated using reference genomes hg19, hg38, and the emerging T2T, with seamless remapping capabilities between them. Features such as gene summaries and links, tissue and cell-specific gene expression data for both adults and fetuses, as well as automated PCR design and integration with tools such as SpliceAI and AlphaMissense, enable users to focus on the biology and the case itself. As we demonstrate, VARista proved effective in narrowing down potential disease-causing variants, prioritizing them effectively, and providing meaningful biological context, facilitating rapid decision-making. VARista stands out as a freely available and comprehensive tool that consolidates various aspects of variant analysis into a single platform that embraces the forefront of genomic advancements. Its design inherently supports a shift in focus from technicalities to critical thinking, thereby promoting better-informed decisions in genetic disease research. Given its unique capabilities and user-centric design, VARista has the potential to become an essential asset for the genomic research community. https://VARista.link.
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Registered trials
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.