Evaluating the effects of imputation on the power, coverage, and cost efficiency of genome-wide SNP platforms.

[1]  Mingyao Li,et al.  Evaluating cost efficiency of SNP chips in genome‐wide association studies , 2008, Genetic epidemiology.

[2]  Zhaohui S. Qin,et al.  A second generation human haplotype map of over 3.1 million SNPs , 2007, Nature.

[3]  E. Birney,et al.  Challenges and standards in integrating surveys of structural variation , 2007, Nature Genetics.

[4]  P. Donnelly,et al.  A new multipoint method for genome-wide association studies by imputation of genotypes , 2007, Nature Genetics.

[5]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[6]  Judy H Cho,et al.  Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis , 2007, Nature Genetics.

[7]  Jonathan C. Cohen,et al.  A Common Allele on Chromosome 9 Associated with Coronary Heart Disease , 2007, Science.

[8]  Lon R Cardon,et al.  Evaluating coverage of genome-wide association studies , 2006, Nature Genetics.

[9]  D. Clayton,et al.  A genome-wide association study of nonsynonymous SNPs identifies a type 1 diabetes locus in the interferon-induced helicase (IFIH1) region , 2006, Nature Genetics.

[10]  C. Power,et al.  Cohort profile: 1958 British birth cohort (National Child Development Study). , 2006, International journal of epidemiology.

[11]  M. Olivier.  A haplotype map of the human genome , 2003, Nature.

[12]  M. Olivier.  A haplotype map of the human genome. , 2003, Nature.

[13]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .