Evidence map›Paper›PMID 19217022›Full record

ArticleGenetic epidemiology2009

The sumLINK statistic for genetic linkage analysis in the presence of heterogeneity.

G B Christensen, S Knight, N J Camp

Abstract read
In one paragraph

Article in Genetic epidemiology, 2009. 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
–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

3 citing papers in PubMed.

  1. Article
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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

3 authors.

G B ChristensenDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, Utah 84108-1266, USA. bryce.christensen@utah.edu
S Knight
N J Camp

Funding

Prostate Cancer Susceptibility: The ICPCG StudyU01CA089600 · NCI · MAYO CLINIC ROCHESTER · PI THIBODEAU, STEPHEN NORMAN · 2002 to 2016
$27.3M
UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
Proteins to Population:A metacluster for BioinformaticsS10RR017214 · NCRR · UNIVERSITY OF UTAH · PI FACELLI, JULIO CESAR · 2002 to 2002
$1.5M
GENETIC ANALYSIS TECHNIQUES FOR COMMON CANCERSK07CA098364 · NCI · UNIVERSITY OF UTAH · PI CAMP, NICOLA J. · 2004 to 2008
$701k
NCI NIH HHS CA89600NCI NIH HHS CA98364NCI NIH HHS K07 CA098364NCI NIH HHS U01 CA089600NCRR NIH HHS 1 S10 RR17214-01NCRR NIH HHS S10 RR017214NIGMS NIH HHS R01 GM031575NIGMS NIH HHS R01GM031575NLM NIH HHS T15 LM007124NLM NIH HHS T15 LM07124
6 · The paper itself

Abstract

We present the "sumLINK" statistic--the sum of multipoint LOD scores for the subset of pedigrees with nominally significant linkage evidence at a given locus--as an alternative to common methods to identify susceptibility loci in the presence of heterogeneity. We also suggest the "sumLOD" statistic (the sum of positive multipoint LOD scores) as a companion to the sumLINK. sumLINK analysis identifies genetic regions of extreme consistency across pedigrees without regard to negative evidence from unlinked or uninformative pedigrees. Significance is determined by an innovative permutation procedure based on genome shuffling that randomizes linkage information across pedigrees. This procedure for generating the empirical null distribution may be useful for other linkage-based statistics as well. Using 500 genome-wide analyses of simulated null data, we show that the genome shuffling procedure results in the correct type 1 error rates for both the sumLINK and sumLOD. The power of the statistics was tested using 100 sets of simulated genome-wide data from the alternative hypothesis from GAW13. Finally, we illustrate the statistics in an analysis of 190 aggressive prostate cancer pedigrees from the International Consortium for Prostate Cancer Genetics, where we identified a new susceptibility locus. We propose that the sumLINK and sumLOD are ideal for collaborative projects and meta-analyses, as they do not require any sharing of identifiable data between contributing institutions. Further, loci identified with the sumLINK have good potential for gene localization via statistical recombinant mapping, as, by definition, several linked pedigrees contribute to each peak.

Indexed as

Genetic LinkageComputer SimulationFalse Positive ReactionsGenomeGenome-Wide Association StudyHumansLod ScoreMaleModels, GeneticModels, StatisticalMolecular EpidemiologyPedigreeProstatic NeoplasmsResearch DesignStatistics as Topic

Identifiers

PMID19217022
PMCPMC3409837

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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.