A new multipoint method for genome-wide association studies by imputation of genotypes

By Jonathan Marchini, Bryan N. Howie, S. Myers, G. McVean, Peter Donnelly. Nature Genetics, 2007

2,734 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/015688f49a26ca19bd67d2299bd16ad0816331cf

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In Genetics

Citations in the corpus

Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences (2016, background): “Plink [43], Snptest [44] and a variety of R packages, including the Bioconductor project [45]) supporting the whole workflow from quality control (QC) of raw genotyping data to analysis, such as association, heritability, genetic risk scoring and burden analyses.”
Using multiple genetic variants as instrumental variables for modifiable risk factors (2012, positive): “It might also be possible to impute missing data for single SNPs by exploiting the LD structure between SNPs in LD with them, as is common in GWAS.(69) In the ALSPAC study, maternal genotypes are available, which could also be used to impute missing offspring genotypes.”
Detection of sharing by descent, long-range phasing and haplotype imputation (2008, methodology): “Apart from being the first procedure that can systematically impute haplotypes into completely untyped individuals, our method can also be used in conjunction with previous methods for the imputation of untyped variants into individuals with other markers type”
ProbABEL package for genome-wide association analysis of imputed data (2010, methodology): “SNPTEST implements a score test based on missing data likelihood [4] allowing for the study of both quantitative and binary outcomes.”
MaCH: Using Sequence and Genotype Data to Estimate Haplotypes and Unobserved Genotypes (2010, methodology): “For example, whereas [Marchini et al., 2007] rely on recombination rates generated by the HapMap Consortium and assume a uniform mutation/error rate for all markers, we estimate ‘‘recombination rates’’ within each dataset and allow ‘‘mutation rates’’ to vary.”
Replication in genome-wide association studies (2009, methodology): “As the number of SNPs typed per region increased, “moving the goalposts” in this fashion contributed to the problem of persistent false positives in the candidate gene literature; by chance, some SNP in the region (not necessarily the SNP that was statistically significant in other studies) would ha”
MultiPhen: Joint Model of Multiple Phenotypes Can Increase Discovery in GWAS (2012, methodology): “Genotypes that were not directly measured were imputed using IMPUTE [22].”
Genome-Wide Association Study of Retinopathy in Individuals without Diabetes (2013, methodology): “org) was used in CHS and SNPTEST v2 [34,35] was used in MESA.”