Evidence map›Paper›PMID 24006871›Full record

ArticleBMC bioinformatics2013

Pathway-PDT: a flexible pathway analysis tool for nuclear families.

Yo Son Park, Michael Schmidt, Eden R Martin, Margaret A Pericak-Vance, Ren-Hua Chung

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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  3. Review
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 3 institutions in 2 countries.

Yo Son ParkDivision of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan. rchung@nhri.org.tw.
Michael Schmidt
Eden R Martin
Margaret A Pericak-Vance
Ren-Hua Chung
Dr. John T. Macdonald Foundation · USNational Health Research Institutes · TWUniversity of Miami · US

Funding

Molecular and Genetic Epidemiology of AutismR01MH080647 · NIMH · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI PERICAK-VANCE, MARGARET A. · 2007 to 2011
$5.9M
NIMH NIH HHS R01 MH080647
6 · The paper itself

Abstract

backgroundPathway analysis based on Genome-Wide Association Studies (GWAS) data has become popular as a secondary analysis strategy. Although many pathway analysis tools have been developed for case-control studies, there is no tool that can use all information from raw genotypes in general nuclear families. We developed Pathway-PDT, which uses the framework of Pedigree Disequilibrium Test (PDT) for general family data, to perform pathway analysis based on raw genotypes in family-based GWAS.

resultsSimulation results showed that Pathway-PDT is more powerful than the p-value based method, ALIGATOR. Pathway-PDT also can be more powerful than the PLINK set-based test when analyzing general nuclear families with multiple siblings or missing parents. Additionally, Pathway-PDT has a flexible and convenient user interface, which allows users to modify their analysis parameters as well as to apply various types of gene and pathway definitions.

conclusionsThe Pathway-PDT method is implemented in C++ with POSIX threads and is computationally feasible for pathway analysis with large scale family GWAS datasets. The Windows binary along with Makefile and source codes for the Linux are available at https://sourceforge.net/projects/pathway-pdt/.

Indexed as

PedigreeSoftwareComputational BiologyGenome-Wide Association StudyGenotypeHumansNuclear Family

Identifiers

PMID24006871
PMCPMC3844459
OpenAlexW2070476370

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.