Evidence map›Paper›PMID 34313777›Full record

ArticleNucleic acids research2021

VarSAn: associating pathways with a set of genomic variants using network analysis.

Xiaoman Xie, Matthew C Kendzior, Xiyu Ge, Liudmila S Mainzer, Saurabh Sinha

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2021. 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
0.2field-weighted citation impact, top 51% of its field
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, 2 citations in OpenAlex.

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

5 authors at 1 institution in 1 country.

Xiaoman XieCenter for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.ORCID 0000-0001-5476-8654
Matthew C KendziorNational Center for Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
Xiyu GeDepartment of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Liudmila S MainzerNational Center for Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
Saurabh SinhaCenter for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
University of Illinois Urbana-Champaign · US

Funding

Quantitative Regulatory Genomics: Networks, CIS-Regulatorycodes, and Phenotypic VariationR35GM131819 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI SINHA, SAURABH · 2019 to 2023
$1.8M
NIGMS NIH HHS R35 GM131819
6 · The paper itself

Abstract

There is a pressing need today to mechanistically interpret sets of genomic variants associated with diseases. Here we present a tool called 'VarSAn' that uses a network analysis algorithm to identify pathways relevant to a given set of variants. VarSAn analyzes a configurable network whose nodes represent variants, genes and pathways, using a Random Walk with Restarts algorithm to rank pathways for relevance to the given variants, and reports P-values for pathway relevance. It treats non-coding and coding variants differently, properly accounts for the number of pathways impacted by each variant and identifies relevant pathways even if many variants do not directly impact genes of the pathway. We use VarSAn to identify pathways relevant to variants related to cancer and several other diseases, as well as drug response variation. We find VarSAn's pathway ranking to be complementary to the standard approach of enrichment tests on genes related to the query set. We adopt a novel benchmarking strategy to quantify its advantage over this baseline approach. Finally, we use VarSAn to discover key pathways, including the VEGFA-VEGFR2 pathway, related to de novo variants in patients of Hypoplastic Left Heart Syndrome, a rare and severe congenital heart defect.

Indexed as

Polymorphism, Single NucleotideSoftwareAlgorithmsBreast NeoplasmsData Interpretation, StatisticalFemaleGenesGenomicsHumansHypoplastic Left Heart SyndromeMaleProstatic NeoplasmsSignal Transduction

Identifiers

PMID34313777
PMCPMC8421213
OpenAlexW3185676725

What OpenQuestion holds

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LicenceCC BY-NC
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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.