Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Analysis of untyped SNPs: maximum likelihood and imputation methods.

Genetic epidemiology - 1 Dec 2010

Hu Y J, Lin D Y

Abstract excerpt

Analysis of untyped single nucleotide polymorphisms (SNPs) can facilitate the localization of disease-causing variants and permit meta-analysis of association studies with different genotyping platforms. We present two approaches for using the linkage disequilibrium structure of an external reference panel to infer the unknown value of an untyped SNP from the observed genotypes of typed SNPs. The...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Computer Simulation
Share to Confidence Intervals
Share to Cross-Sectional Studies

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Diabetes Mellitus, Type 1

Share to Environment

Share to Likelihood Functions

Share to Software

Source

Open in PubMed Open full text

Identifiers

PMID: 21104886
DOI: 10.1002/gepi.20527
PMCID: PMC3030127

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Analysis of untyped SNPs: maximum likelihood and imputation methods.PMID 21104886Read ↗

Accurate Imputation of Untyped Variants from Deep Sequencing Data.Semantic proximity Read ↗

Imputation of missing genotypes: an empirical evaluation of IMPUTE.Semantic proximity Read ↗

Analyses and comparison of imputation-based association methods.Semantic proximity Read ↗

Analyses and comparison of accuracy of different genotype imputation methods.Semantic proximity Read ↗

Simple and efficient analysis of disease association with missing genotype data.Semantic proximity Read ↗

Fast and robust association tests for untyped SNPs in case-control studies.Semantic proximity Read ↗

Practical considerations for imputation of untyped markers in admixed populations.Semantic proximity Read ↗

Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies.Semantic proximity Read ↗

Imputation-Aware Tag SNP Selection To Improve Power for Large-Scale, Multi-ethnic Association Studies.Semantic proximity Read ↗

Advantages of genotype imputation with ethnically matched reference panel for rare variant association analysesSemantic proximity Read ↗

Imputation-based assessment of next generation rare exome variant arrays.Semantic proximity Read ↗

Accurate imputation of rare and common variants in a founder population from a small number of sequenced individuals.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.