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Main quality control functions

perIndividualQC()

Quality control for all individuals in plink-dataset

perMarkerQC()

Quality control for all markers in plink-dataset

overviewPerIndividualQC()

Overview of per sample QC

overviewPerMarkerQC()

Overview of per marker QC

cleanData()

Create plink dataset with individuals and markers passing quality control

Individual quality control functions

Functions for step-by-step per-individual quality control

check_sex()

Identification of individuals with discordant sex information

check_relatedness()

Identification of related individuals

check_het_and_miss()

Identification of individuals with outlying missing genotype or heterozygosity rates

check_ancestry()

Identification of individuals of divergent ancestry

Marker quality control functions

Functions for step-by-step per-marker quality control

check_snp_missingness()

Identification of SNPs with high missingness rate

check_maf()

Identification of SNPs with low minor allele frequency

check_hwe()

Identification of SNPs showing a significant deviation from Hardy-Weinberg- equilibrium (HWE)

Quality control helper functions

Helper functions for step-by-step per-individual quality control: accesible to the user, but recommended use via per-individual check_* functions.

run_check_sex()

Run PLINK sexcheck

evaluate_check_sex()

Evaluate results from PLINK sex check.

run_check_heterozygosity()

Run PLINK heterozygosity rate calculation

run_check_missingness()

Run PLINK missingness rate calculation

evaluate_check_het_and_miss()

Evaluate results from PLINK missing genotype and heterozygosity rate check.

run_check_relatedness()

Run PLINK IBD estimation

evaluate_check_relatedness()

Evaluate results from PLINK IBD estimation.

run_check_ancestry()

Run PLINK principal component analysis

evaluate_check_ancestry()

Evaluate results from PLINK PCA on combined study and reference data

General helper functions

checkPlink()

Check PLINK software access

testNumerics()

Test lists for different properties of numerics

relatednessFilter()

Remove related individuals while keeping maximum number of individuals