Evidence map›Paper›PMID 16451614›Full record

ArticleBMC genetics2005

Effect of genotyping error in model-free linkage analysis using microsatellite or single-nucleotide polymorphism marker maps.

Cheryl L Thompson, Dan Baechle, Qing Lu, George Mathew, Yeunjoo Song, Sudha K Iyengar, Courtney Gray-McGuire, Katrina A B Goddard

Abstract read
In one paragraph

Article in BMC genetics, 2005. 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
–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

0 citing papers in PubMed.

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

8 authors.

Cheryl L ThompsonDepartment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA. clw8@cwru.edu
Dan Baechle
Qing Lu
George Mathew
Yeunjoo Song
Sudha K Iyengar
Courtney Gray-McGuire
Katrina A B Goddard

Funding

X-LINKED EXTENSION OF THE REVISED HASEMAN-ELSTON ALGORITHM FOR LINKAGE ANALYSISP41RR003655 · NCRR · LOUISIANA STATE UNIV HSC NEW ORLEANS · PI ELSTON, ROBERT C. · 1987 to 2011
$11.5M
BIOMETRIC-GENETIC ANALYSIS OF CARDIOVASCULAR DISEASET32HL007567 · NHLBI · LOUISIANA STATE UNIV HSC NEW ORLEANS · PI ZHU, XIAOFENG · 1985 to 2021
$6.0M
GENETIC ANALYSIS OF MULTIFACTORIAL TRAITSR37GM028356 · NIGMS · CASE WESTERN RESERVE UNIVERSITY · PI ELSTON, ROBERT C. · 1998 to 2007
$2.9M
Robust Linkage Methods for Human Pedigree DataR01HG001577 · NHGRI · CASE WESTERN RESERVE UNIVERSITY · PI GODDARD, KATRINA A · 2001 to 2004
$758k
ROBUST LINKAGE METHODS FOR HUMAN PEDIGREE DATAR29HG001577 · NHGRI · CASE WESTERN RESERVE UNIVERSITY · PI OLSON, JANE M. · 1996 to 2000
$101k
GENETIC ANALYSIS OF MULTIFACTORIAL TRAITSR01GM028356 · NIGMS · LOUISIANA STATE UNIV HSC NEW ORLEANS · PI ELSTON, ROBERT C. · 1985 to 1997
–
NCRR NIH HHS P41 RR003655NCRR NIH HHS RR03655NHGRI NIH HHS HG01577NHGRI NIH HHS R01 HG001577NHGRI NIH HHS R29 HG001577NHLBI NIH HHS HL07567NHLBI NIH HHS T32 HL007567NIGMS NIH HHS GM28356NIGMS NIH HHS R01 GM028356NIGMS NIH HHS R37 GM028356
6 · The paper itself

Abstract

Errors while genotyping are inevitable and can reduce the power to detect linkage. However, does genotyping error have the same impact on linkage results for single-nucleotide polymorphism (SNP) and microsatellite (MS) marker maps? To evaluate this question we detected genotyping errors that are consistent with Mendelian inheritance using large changes in multipoint identity-by-descent sharing in neighboring markers. Only a small fraction of Mendelian consistent errors were detectable (e.g., 18% of MS and 2.4% of SNP genotyping errors). More SNP genotyping errors are Mendelian consistent compared to MS genotyping errors, so genotyping error may have a greater impact on linkage results using SNP marker maps. We also evaluated the effect of genotyping error on the power and type I error rate using simulated nuclear families with missing parents under 0, 0.14, and 2.8% genotyping error rates. In the presence of genotyping error, we found that the power to detect a true linkage signal was greater for SNP (75%) than MS (67%) marker maps, although there were also slightly more false-positive signals using SNP marker maps (5 compared with 3 for MS). Finally, we evaluated the usefulness of accounting for genotyping error in the SNP data using a likelihood-based approach, which restores some of the power that is lost when genotyping error is introduced.

Indexed as

Models, GeneticChromosome MappingFalse Positive ReactionsGenotypeHumansLikelihood FunctionsMicrosatellite RepeatsPolymorphism, Single NucleotideRecombination, GeneticResearch Design

Identifiers

PMID16451614
PMCPMC1866781

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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.