PLINK a toolset for whole genome association and ：Plink的全基因组关联的工具和.pptVIP

PLINK: a toolset for whole genome association analysis Shaun Purcell shaun@pngu.mgh.harvard.edu Center for Human Genetic Research, Massachusetts General Hospital Broad Institute of Harvard MIT Data management Summary statistics Population stratification Association analysis Linkage disequilibrium and haplotype analysis Shared segment analysis Copy number analysis Data management Recode dataset (A,C,G,T → 1,2) Reorder, reformat dataset Flip DNA strand Extract/remove individuals/SNPs Swap in new phenotypes, covariates Filter on covariates Merge 2 or more filesets Summary statistics Filters and reports for standard metrics Genotyping rate Allele, genotype, haplotype frequencies Hardy-Weinberg Mendel errors Tests of non-random missingness by phenotype and by (unobserved) genotype Individual homozygosity estimates Check/impute sex based on X chromosome LD-based detection of strand flips A/T and C/G SNPs potentially ambiguous Automated search for plate effects w/ subsequent masking of specific SNP/individual genotypes Estimation of IBD sharing (relatedness) Association analysis Population-based Allelic, trend, genotypic, Fisher’s exact Stratified tests (Cochran-Mantel-Haenszel, Breslow-Day) Linear logistic regression models multiple covariates, interactions, joint tests, etc Family-based Disease traits: TDT / sib-TDT Continuous traits: QFAM (between/within model, QTDT) Permutation procedures “adaptive”, max(T), gene-dropping, between/within, rank-based, within-cluster Multilocus tests Haplotype estimation, set-based tests, Hotelling’s T2, epistasis Acknowledgements Broad Institute Medical Population Genetics Program Julian Maller Dave Bender Ben Neale Andrew Kirby Paul de Bakker Itsik Pe’er Ben Voight David Altshuler Pamela Sklar Mark Daly PLINK development Kathe Todd-Brown Douglas Ruderfer Lori Thomas Manuel Ferreira Pak Sham ENDGAME (NIH) PLINK practical 1 Data cleaning and association testing In this practical we will analyse a simulated d