Evidence map›Paper›PMID 39994572›Full record

ArticleBMC genomics2025

MARSweb: a fully automated web service for set-based association testing.

Taegun Kim, Jaeseung Song, Jong Wha J Joo

Abstract read
In one paragraph

Article in BMC genomics, 2025. 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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2 · The registry

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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

3 authors.

Taegun KimDivision of AI Software Convergence, Dongguk University-Seoul, Seoul, 04620, South Korea.
Jaeseung SongDepartment of Life Science, Dongguk University-Seoul, Seoul, 04620, South Korea.
Jong Wha J JooDivision of AI Software Convergence, Dongguk University-Seoul, Seoul, 04620, South Korea. jwjjoo@dgu.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the successes in GWAS, there is still a large gap between the known heritability and the part explained by the SNPs identified by GWAS. Set-based analysis is one of the approaches that has tried to identify associations between multiple variants in a locus a trait, leveraging allelic heterogeneity to increase power in association testing. MARS is a set-based analysis method that integrates likelihood ratio test with a recently developed fine mapping technique to accurately account for causal status of variants in a risk locus. Unfortunately, due to its complex running process, time complexity, and the requirement of high-performance computing resources, it is not widely used.

resultsTo address these issues, we proposed a fully automated web-based analysis service, MARSweb. By providing a web service, we minimized the effort required for initial configuration. Additionally, users can perform analyses by simply uploading their data without needing to familiarize themselves with intricate analysis procedures. Furthermore, it facilitates easier interpretation of results by integrating advanced visualization tools. We confirmed the performance of MARSweb by detecting eGenes and performing pathway analysis of the genes using a Yeast Dataset.

conclusionsMARSweb is a web-based analysis service that fully automates set-based analysis. It offers an intuitive user interface, making complex analyses more accessible while significantly reducing processing time for enhanced efficiency. MARSweb is available for use at http://cblab.dongguk.edu/MARSweb and its source code is available at https://github.com/DGU-CBLAB/MARSweb .

Indexed as

Computational BiologyGenome-Wide Association StudyInternetSoftwareHumansPolymorphism, Single NucleotideSaccharomyces cerevisiaeAllelic heterogeneityGWASLikelihood ratio testSet-based analysisWeb-based

Identifiers

PMID39994572
PMCPMC11853308

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LicenceCC BY-NC-ND
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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.