Version Compatibility

Binary Format (Recommended)

PLINK 2.0 Format

Text Format (Legacy)

Format Conversion

VCF to PLINK Binary

# PLINK 1.9
plink --vcf input.vcf.gz --make-bed --out output

# PLINK 2.0
plink2 --vcf input.vcf.gz --make-bed --out output

# With sample ID handling
plink2 --vcf input.vcf.gz --double-id --make-bed --out output

PLINK Binary to VCF

# PLINK 1.9
plink --bfile input --recode vcf --out output

# PLINK 2.0
plink2 --bfile input --export vcf --out output

# Compressed VCF
plink2 --bfile input --export vcf bgz --out output

PED/MAP to Binary (PLINK 1.9 Only)

# PLINK 1.9 (PLINK 2.0 doesn't support .ped/.map directly)
plink --file input --make-bed --out output

Binary to PED/MAP

# PLINK 1.9
plink --bfile input --recode --out output

# PLINK 2.0
plink2 --bfile input --export ped --out output

PLINK 1.9 to 2.0 Format

# Convert to PGEN format
plink2 --bfile input --make-pgen --out output

# Convert back to BED
plink2 --pfile input --make-bed --out output

Quality Control Filtering

MAF Filter (Minor Allele Frequency)

# Remove variants with MAF < 0.01
plink --bfile input --maf 0.01 --make-bed --out output

# PLINK 2.0
plink2 --bfile input --maf 0.01 --make-bed --out output

# Remove rare variants (MAF < 0.05)
plink2 --bfile input --maf 0.05 --make-bed --out output

Genotyping Rate Filters

# Per-variant missing rate (remove if >5% missing)
plink2 --bfile input --geno 0.05 --make-bed --out output

# Per-sample missing rate (remove if >5% missing)
plink2 --bfile input --mind 0.05 --make-bed --out output

Hardy-Weinberg Equilibrium Filter

# Remove variants with HWE p-value < 1e-6
plink2 --bfile input --hwe 1e-6 --make-bed --out output

# Different threshold for cases vs controls
plink2 --bfile input --hwe 1e-6 --hwe-all --make-bed --out output

Combined QC Pipeline

# Standard QC filtering
plink2 --bfile input \
    --maf 0.01 \
    --geno 0.05 \
    --mind 0.05 \
    --hwe 1e-6 \
    --make-bed --out qc_filtered

Sample and Variant Selection

Keep/Remove Samples

# Keep specific samples (samples.txt: FID IID per line)
plink2 --bfile input --keep samples.txt --make-bed --out output

# Remove specific samples
plink2 --bfile input --remove samples.txt --make-bed --out output

# Keep single sample
plink2 --bfile input --keep-fam sample_id --make-bed --out output

Extract/Exclude Variants

# Extract specific variants (variants.txt: variant IDs)
plink2 --bfile input --extract variants.txt --make-bed --out output

# Exclude specific variants
plink2 --bfile input --exclude variants.txt --make-bed --out output

# Extract by range
plink2 --bfile input --extract range chr1:1000000-2000000 --make-bed --out output

Chromosome Selection

# Single chromosome
plink2 --bfile input --chr 22 --make-bed --out chr22

# Multiple chromosomes
plink2 --bfile input --chr 1-22 --make-bed --out autosomes

# Exclude chromosome
plink2 --bfile input --not-chr 23,24,25,26 --make-bed --out autosomes

Allele Frequency

# PLINK 1.9 (MAF-based)
plink --bfile input --freq --out output

# PLINK 2.0 (ALT allele frequency - not MAF!)
plink2 --bfile input --freq --out output

# PLINK 2.0 with MAF
plink2 --bfile input --freq cols=+mac,+mafreq --out output

Missing Data Statistics

# Per-sample and per-variant missing rates
plink2 --bfile input --missing --out output

# Output files:
# output.smiss - sample missing rates
# output.vmiss - variant missing rates

Sex Check

Verify reported sex matches X chromosome heterozygosity.

# PLINK 1.9
plink --bfile input --check-sex --out sex_check

# PLINK 2.0
plink2 --bfile input --split-par hg38 --check-sex --out sex_check

Interpret Results

import pandas as pd

sex = pd.read_csv('sex_check.sexcheck', sep='\s+')

problems = sex[sex['STATUS'] == 'PROBLEM']
print(f'Sex mismatches: {len(problems)}')

# F statistic: <0.2 = female, >0.8 = male, between = ambiguous
# PEDSEX: reported sex (1=male, 2=female, 0=unknown)
# SNPSEX: inferred sex (1=male, 2=female, 0=undetermined)

Update or Remove

# Update sex from check results
plink2 --bfile input --update-sex sex_check.sexcheck col-num=4 --make-bed --out updated

# Remove sex mismatches
awk '$5 == "PROBLEM" {print $1, $2}' sex_check.sexcheck > sex_problems.txt
plink2 --bfile input --remove sex_problems.txt --make-bed --out output

Sample Information

Update Phenotypes

# phenotypes.txt: FID IID pheno (1=control, 2=case, -9=missing)
plink2 --bfile input --pheno phenotypes.txt --make-bed --out output

# Quantitative phenotype
plink2 --bfile input --pheno phenotypes.txt --make-bed --out output

Update Sex

# sex.txt: FID IID sex (1=male, 2=female, 0=unknown)
plink2 --bfile input --update-sex sex.txt --make-bed --out output

Update Sample IDs

# ids.txt: old_FID old_IID new_FID new_IID
plink2 --bfile input --update-ids ids.txt --make-bed --out output

Merging Datasets

# Merge two datasets (PLINK 1.9)
plink --bfile data1 --bmerge data2.bed data2.bim data2.fam --make-bed --out merged

# Merge list of datasets
plink --bfile data1 --merge-list merge_list.txt --make-bed --out merged
# merge_list.txt contains: data2.bed data2.bim data2.fam (one set per line)

# Handle strand flips
plink --bfile data1 --bmerge data2 --make-bed --out merged
# If error: plink --bfile data2 --flip missnps.txt --make-bed --out data2_flipped

Variant Information

Set Variant IDs

# Set ID based on position
plink2 --bfile input --set-all-var-ids @:#:\$r:\$a --make-bed --out output
# Format: chr:pos:ref:alt

Update Variant Names

# update.txt: old_id new_id
plink2 --bfile input --update-name update.txt --make-bed --out output

PLINK 2.0 vs 1.9 Summary

Related Skills

• association-testing - GWAS with filtered data
• population-structure - PCA after QC
• variant-calling/vcf-basics - VCF format before conversion