Evidence map›Paper›PMID 22611130›Full record

ArticleBioinformatics (Oxford, England)2012

regSNPs: a strategy for prioritizing regulatory single nucleotide substitutions.

Mingxiang Teng, Shoji Ichikawa, Leah R Padgett, Yadong Wang, Matthew Mort, David N Cooper, Daniel L Koller, Tatiana Foroud, Howard J Edenberg, Michael J Econs and 1 more

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

11 authors.

Mingxiang TengSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Shoji Ichikawa
Leah R Padgett
Yadong Wang
Matthew Mort
David N Cooper
Daniel L Koller
Tatiana Foroud
Howard J Edenberg
Michael J Econs
Yunlong Liu

Funding

NEUROBEHAVIORAL STUDY OF SCHIZOPHRENIAR01MH042191 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI GUR, RAQUEL E · 1987 to 2018
$7.1M
Identification of genes that affect peak BMD in men and womenR01AG041517 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI ECONS, MICHAEL J · 2011 to 2015
$2.9M
Elucidating CIS-Acting Elements Regulating Alcohol-Induced Alternative SplicingR21AA017941 · NIAAA · INDIANA UNIVERSITY INDIANAPOLIS · PI EDENBERG, HOWARD J, LIU, YUNLONG · 2009 to 2010
$424k
NIAAA NIH HHS AA017941NIAAA NIH HHS R21 AA017941NIA NIH HHS AG041517NIA NIH HHS R01 AG041517NIMH NIH HHS R01 MH042191
6 · The paper itself

Abstract

motivationOne of the fundamental questions in genetics study is to identify functional DNA variants that are responsible to a disease or phenotype of interest. Results from large-scale genetics studies, such as genome-wide association studies (GWAS), and the availability of high-throughput sequencing technologies provide opportunities in identifying causal variants. Despite the technical advances, informatics methodologies need to be developed to prioritize thousands of variants for potential causative effects.

resultsWe present regSNPs, an informatics strategy that integrates several established bioinformatics tools, for prioritizing regulatory SNPs, i.e. the SNPs in the promoter regions that potentially affect phenotype through changing transcription of downstream genes. Comparing to existing tools, regSNPs has two distinct features. It considers degenerative features of binding motifs by calculating the differences on the binding affinity caused by the candidate variants and integrates potential phenotypic effects of various transcription factors. When tested by using the disease-causing variants documented in the Human Gene Mutation Database, regSNPs showed mixed performance on various diseases. regSNPs predicted three SNPs that can potentially affect bone density in a region detected in an earlier linkage study. Potential effects of one of the variants were validated using luciferase reporter assay.

Indexed as

Polymorphism, Single NucleotidePromoter Regions, GeneticArea Under CurveBinding SitesComputational BiologyDatabases, GeneticGenetic LinkageGenome, HumanGenome-Wide Association StudyHEK293 CellsHumansPhenotypeROC CurveTranscription FactorsTranscription Factors

Identifiers

PMID22611130
PMCPMC3389767

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.