Score tests for association between traits and haplotypes when linkage phase is ambiguous.

By Daniel J. Schaid, Charles Rowland, David E. Tines, R. Jacobson, Gregory A. Poland. American Journal of Human Genetics, 2002

1,889 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ae140adfb374c19b633b937082e82af189a66e2b

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Citations in the corpus

A new algorithm for haplotype‐based association analysis: the Stochastic‐EM algorithm (2004, background): “…from genotypic data in unrelated individuals (Chiano & Clayton, 1998; Excofﬁer & Slatkin, 1995; Li, 2001; Li et al. 2002; Lin et al. 2002; Liu et al. 2001; Schaid et al. 2002; Seaman et al. 2002; Stephens et al. 2001; Tregouet et al. 2002; Xu et al. 2002; Zaykin et al. 2002; Zhao & Sham, 2002).”
Likelihood-Based Inference on Haplotype Effects in Genetic Association Studies (2006, background): “Building on the earlier work of Schaid et al. (2002), Lake et al. (2003) discussed likelihoodbased inference for cross-sectional studies under generalized linear models.”
The future of association studies: gene-based analysis and replication. (2004, methodology): “A genewide approach also requires the analysis of multilocus genotype data; methods for doing this, taking into account phase uncertainty, are being rapidly developed (Schaid et al. 2002; Zaykin et al. 2002; Zhang et al. 2002b; North et al. 2003; Seltman et al. 2003; Tanck et al. 2003; Thomas et al.”
A tutorial on statistical methods for population association studies (2006, background): “Instead of inferring haplotypes in a separate step, ambiguous phase can be directly incorporate”
Genotype Imputation (2009, background): “The intuition that short stretches of haplotype provide useful information about untyped genetic markers provides the justification for the power gains suggested for many haplotype analysis strategies (22, 60, 91, 115).”
Genotype and SNP calling from next-generation sequencing data (2011, methodology): “and methods used for haplotype data, such as score statistic”
Pedigree disequilibrium tests for multilocus haplotypes (2003, methodology): “In studies of unrelated subjects, several similar methods have emerged which use the expectation-maximization (E-M) algorithm to estimate haplotype frequencies from unphased genotype data [Zhao et al., 2000; Schaid et al., 2002; Zaykin et al., 2002].”
Nuclear DNA analyses in genetic studies of populations: practice, problems and prospects (2003, background): “Several expectation–maximization (EM)-based algorithms were introduced recently (e.g. Excoffier & Slatkin 1995; Hawley & Kidd 1995; Long et al. 1995; Schaid et al. 2002) to carry out a maximum-likelihood estimation of haplotypes and haplotype frequencies.”