Evidence map›Paper›PMID 24533837›Full record

ArticleBMC bioinformatics2014

PSEUDOMARKER 2.0: efficient computation of likelihoods using NOMAD.

Edward Michael Gertz, Tero Hiekkalinna, Sébastien Le Digabel, Charles Audet, Joseph D Terwilliger, Alejandro A Schäffer

Abstract read
In one paragraph

Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  3. Review
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  6. Article
  7. PeerJ · 2017
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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

6 authors.

Edward Michael GertzNational Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.
Tero Hiekkalinna
Sébastien Le Digabel
Charles Audet
Joseph D Terwilliger
Alejandro A Schäffer

Funding

Case Studies In GeneticsZIALM000097 · NLM · NATIONAL LIBRARY OF MEDICINE · PI SCHAFFER, ALEJANDRO A · 2009 to 2019
$4.6M
Gene-Environment Interactions in Cognition in Venezuelan FamiliesR01AG036469 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CHACON, INARA, MAESTRE, GLADYS E. · 2011 to 2015
$2.7M
Inferring phenogentic mechanisms in psychiatric and other complex traitsR01MH084995 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI TERWILLIGER, JOSEPH DOUGLAS · 2009 to 2012
$1.6M
Intramural NIH HHSNIA NIH HHS AG036469NIMH NIH HHS MH084995NIMH NIH HHS R01 MH084995
6 · The paper itself

Abstract

backgroundPSEUDOMARKER is a software package that performs joint linkage and linkage disequilibrium analysis between a marker and a putative disease locus. A key feature of PSEUDOMARKER is that it can combine case-controls and pedigrees of varying structure into a single unified analysis. Thus it maximizes the full likelihood of the data over marker allele frequencies or conditional allele frequencies on disease and recombination fraction.

resultsThe new version 2.0 uses the software package NOMAD to maximize likelihoods, resulting in generally comparable or better optima with many fewer evaluations of the likelihood functions.

conclusionsAfter being modified substantially to use modern optimization methods, PSEUDOMARKER version 2.0 is more robust and substantially faster than version 1.0. NOMAD may be useful in other bioinformatics problems where complex likelihood functions are optimized.

Indexed as

SoftwareComputational BiologyDiseaseGene FrequencyGenetic LinkageHumansLikelihood FunctionsLinkage DisequilibriumPedigreeSequence Analysis, DNA

Identifiers

PMID24533837
PMCPMC3932042

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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.