Evidence map›Paper›PMID 20517342›Full record

ReviewNature reviews. Genetics2010

Genotype imputation for genome-wide association studies.

Jonathan Marchini, Bryan Howie

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 980 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
980citing papers in PubMed, 9 pooled it
–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

980 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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  6. Genome-Wide Association and Two-Sample Mendelian Randomization Analyses of Plasma Ghrelin and Gastrointestinal Cancer Risk.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
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920 more citing papers are in PubMed but not listed here.

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

2 authors.

Jonathan MarchiniDepartment of Statistics, University of Oxford, Oxford, UK. marchini@stats.ox.ac.uk
Bryan Howie

Funding

Medical Research Council G0801823
6 · The paper itself

Abstract

In the past few years genome-wide association (GWA) studies have uncovered a large number of convincingly replicated associations for many complex human diseases. Genotype imputation has been used widely in the analysis of GWA studies to boost power, fine-map associations and facilitate the combination of results across studies using meta-analysis. This Review describes the details of several different statistical methods for imputing genotypes, illustrates and discusses the factors that influence imputation performance, and reviews methods that can be used to assess imputation performance and test association at imputed SNPs.

Indexed as

Genome-Wide Association StudyBiostatisticsGenotypeModels, GeneticPolymorphism, Single Nucleotide

Identifiers

PMID20517342

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.