1. BST 775 Lecture PLINK – A Popular Toolset for GWAS
Guodong Wu
SSG, Department of Biostatistics
University of Alabama at Birmingham
September 24, 2013

2. Overview Designed for GWAS and population-based linkage analysis.
Developed by Shaun Purcell*, current version V1.07.
Why the toolset is so popular?
Store the GWAS data sets, which is too large for SAS, R, or other statistical packages.
Well developed guideline and toolsets for Dataset Management and Quality Control
Platform for various association methods
* Purcell et al 2007, AJHG

3. Overview Data management Summary statistics Quality Control
Association Test

4. PLINK in GWAS workflow Experimental Design & Sample Collection
Cell Intensity Files for each chip
GeneChip Scanner
Summary statistics and quality control
Phenotype, sex and other covariates
Assessment of population stratification
Whole genome SNP-based association
Further exploration of ‘hits’
Visualization and follow-up

5. Data Format PED and MAP format Transposed format SNP information
SNPs →
SNP information
1 snp
X snp
Y snp
XY snp
MT snp
P1 A A A C C G T T A A T T
P2 A C A A C G G T A C T T
P3 C C A C G G T T A A T T
P4 C C A A G G G T A A T T
←People
Transposed format
People →
People information
S1 A A A C C C C C
S2 A C A A A C A A
S3 C G C G G G G G
S4 T T C G T T G T
S5 A A G T A A A A
S6 T T A C T T T T
←SNPs
P1 …
P2 …
P3 …
P4 …
P5 …
Compact binary format

6. Data management Recode dataset (A,C,G,T → 1,2)
Reorder, reformat dataset
Flip DNA strand
Extract/remove individuals/SNPs
New phenotypes, covariates as extra file
Merge 2 or more data sets

7. Summary and QC Hardy-Weinberg test Mendel errors Missing genotypes
Allele frequencies
Tests of non-random missingness
by phenotype and by (unobserved) genotype
Sex Check
Pairwise IBD estimates

8. Mendel errors An exact test by default.
plink --file data --hardy
An exact test by default.
In Case control study, the Control group typically needs more lenient threshold (eg. P-value < 1e-3)

9. Mendel errors
plink --file data --mendel
Genotyping error when child’s genotype is not inherited from the parents, according to mendel’s law
Output as
Output the error rate for each SNP and each individual
Code Pat , Mat -> Offspring
AA , AA -> AB
BB , BB -> AB
BB , ** -> AA
** , BB -> AA
BB , BB -> AA
AA , ** -> BB
** , AA -> BB
AA , AA -> BB

10. Missingness and Allele Frequency Output each SNP’s allele frequency
plink --file data --missing
Output the missing rate per SNP and per individual.
plink --file data --freq
Output each SNP’s allele frequency

11. Is the missingness random?
plink --file data –-test-missing
Test whether the SNP is randomly missing between case and control status.
plink --file data -–test-mishap
Test whether the SNP is randomly missing based on observed genotyped nearby SNPs.
Assume dense SNP genotyping.
Use haplotype and LD information in tests.

12. Sex Check
plink --file data –check-sex
Use X chromosome data heterozygosity rates to determine sex, and then compare with the observed sex.

13. Pairwise IBD sharing (relatedness)
Most recent common ancestor from
homogeneous random mating population
Parents AB AC AB AC
IBS = 1
IBD = 0 AB AC
PLINK tutorial, October 2006; Shaun Purcell,

14. Relatedness Check
plink --file data –-genome
The Genome-wide information, typically do not need whole-genome SNPs.
Typically 100K independent SNPs are enough.

16. Association methods in PLINK
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

17. An Example: logistic Regression
plink --maf exclude nonautosomalSNPs.txt --out AllAssoc --bfile bdata --remove exclusions.txt --logistic --hide-covar --pheno IChipCovs.txt --pheno-name cas_con --covar IChipCovs.txt --covar-name Sex,EurAdmix

18. An Example: logistic Regression Result

19. Cardinal rules in PLINK
Always consult the log file, console output
Also consult the web documentation
regularly
PLINK has no memory
each run loads data anew, previous filters lost
Exact syntax and spelling is important
“minus minus” …
PLINK tutorial, October 2006; Shaun Purcell,