Evidence map›Paper›PMID 42146374›Full record

ArticlebioRxiv : the preprint server for biology2026

SNPWay: streamlined SNP-to-function and pathway over-representation analysis.

Bryan Queme, Ayaan Kakkar, Anushya Muruganujan, Paul D Thomas, James W Gauderman, Huaiyu Mi

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

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.

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

6 authors.

Bryan QuemeDivision of Biostatistics and Health Data Science, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0000-0003-1509-9982
Ayaan KakkarDivision of Computer Science, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Anushya MuruganujanDivision of Biostatistics and Health Data Science, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90089, USA.
Paul D ThomasDivision of Biostatistics and Health Data Science, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90089, USA.
James W GaudermanDivision of Biostatistics and Health Data Science, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90089, USA.
Huaiyu MiDivision of Biostatistics and Health Data Science, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0000-0001-8721-202X

Funding

Statistical Methods for Integrative Genomics in CancerP01CA196569 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI David V Conti · 2016 to 2026
$25.5M
NCI NIH HHS P01 CA196569
6 · The paper itself

Abstract

Motivation: Post-GWAS interpretation frequently requires translating variant lists (e.g., lead SNPs, clumped loci, credible sets, or curated panels) into pathway and functional hypotheses. In practice, obtaining pathway and functional over-representation results from SNP inputs often requires stitching together multiple tools for variant annotation, regulatory annotation, gene identifier handling, and statistical testing. This integration burden can reduce reproducibility and restrict end-to-end analysis to groups with dedicated bioinformatics support. Summary: We present SNPWay, a web server and R package that performs end-to-end SNP-to-function and pathway over-representation analysis in a single standardized workflow. SNPWay accepts rsIDs, VCF files, or hg19/GRCh37 genomic coordinates. It queries Annotation Query (AnnoQ) to obtain SNP-to-gene mappings from ANNOVAR, SnpEff, and VEP under both Ensembl and RefSeq gene models, and incorporates enhancer-gene links via PEREGRINE to augment mappings for noncoding variants. SNPWay aggregates mapped genes into a single, non-redundant, combined gene list and submits it to PANTHER for over-representation testing against the Homo sapiens reference list, returning over-represented pathways and functional categories (e.g., Gene Ontology) with direct links for interactive exploration in PANTHER. SNPWay's modular architecture is designed for extensibility, enabling incorporation of additional analysis methods in future releases. A step-by-step walkthrough is provided in Supplementary Data.

Identifiers

PMID42146374
PMCPMC13174595

What OpenQuestion holds

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LicenceCC BY
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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.