Package index • radr

Core workflow

Inspect a new dataset, run guided exploration, and review its state.

Investigate missingness, duplicates, mixed samples, marker behaviour, and data origin before filtering.

detect_all_missing(): Detect markers with all missing genotypes
detect_allele_problems(): Detect alternate allele problems
detect_biallelic_problems(): Detect biallelic problems
detect_duplicate_genomes(): Compute pairwise genome similarity or distance between individuals to highligh potential duplicate individuals
detect_het_outliers(): Detect heterozygotes outliers and estimate miscall rate
detect_inversions(): Detect candidate inversion-associated genomic regions
detect_mixed_genomes(): Detect mixed genomes
detect_paralogs(): Detect paralogs
detect_ref_genome(): Detect whether a dataset is reference-guided or de novo assembled

Apply explicit quality-control and marker-selection decisions to GDS data.

filter_individuals(): Filter individuals based on genotyping/missingness rate, heterozygosity and total coverage
filter_genotyping(): Filter markers based on genotyping / missing rate
filter_coverage(): Filter markers mean coverage
filter_ma(): MAC, MAF and MAD filter
filter_het(): Heterozygosity filter
filter_fis(): Fis filter
filter_hwe(): Filter markers based on Hardy-Weinberg Equilibrium
filter_ld(): GBS/RADseq short and long distance linkage disequilibrium pruning
filter_monomorphic(): Filter monomorphic markers
filter_common_markers(): Filter common markers between strata
filter_dart_reproducibility(): Filter data based on DArT reproducibility statistics
filter_snp_number(): Filter SNP number per locus/read
filter_snp_position_read(): Filter markers/SNP based on their position on the read

Retain or exclude selected samples, markers, and individual genotypes.

Apply selected filters directly to VCF files before or outside the GDS workflow.

filter_genotyping_vcf(): Filter SNPs in a VCF based on genotyping / missing rate (bcftools)
filter_mac_vcf(): Filter low-MAC variants in a VCF using bcftools (AC-based)
filter_monomorphic_vcf(): Filter monomorphic SNPs in a VCF using bcftools (AC/AN-based)

Calculate diversity, differentiation, relatedness, and private variation.

allele_frequencies(): Compute allele frequencies per markers and populations
beta_estimator(): Estimate population-specific beta
ibdg_fh(): FH measure of IBDg
pi(): Nucleotide diversity
private_alleles(): Find private alleles
private_haplotypes(): private haplotypes

Investigate specialized marker classes and run external analytical workflows.

Compatibility names retained for older scripts; use the recommended replacement documented on each page.