run_haplotyping: Cluster SNPs and identify haplotypes

In crosshap: Local Haplotype Clustering and Visualization

Cluster SNPs and identify haplotypes

Description

run_haplotyping() performs density-based clustering of SNPs in region of interest to identify Marker Groups. Individuals are classified by haplotype combination based on shared combinations of Marker Group alleles. Returns a haplotyping object (HapObject), which can be used as input to build clustering tree for epsilon optimization using clustree_viz(), and can be visualized with reference to phenotype and metadata using crosshap_viz().

Usage

run_haplotyping(
  vcf,
  LD,
  pheno,
  metadata = NULL,
  epsilon = c(0.2, 0.4, 0.6, 0.8, 1),
  MGmin = 30,
  minHap = 9,
  hetmiss_as = "allele",
  het_phenos = FALSE,
  keep_outliers = FALSE
)

Arguments

vcf	Input VCF for region of interest.
LD	Pairwise correlation matrix of SNPs in region (e.g. from PLINK).
pheno	Input numeric phenotype data for each individual.
metadata	Metadata input (optional).
epsilon	Epsilon values for clustering SNPs with DBscan.
MGmin	Minimum SNPs in marker groups, MinPts parameter for DBscan.
minHap	Minimum nIndividuals in a haplotype combination.
hetmiss_as	If hetmiss_as = "allele", heterozygous-missing SNPs './N' are recoded as 'N/N', if hetmiss_as = "miss", the site is recoded as missing.
het_phenos	When FALSE, phenotype associations for SNPs are calculated from reference and alternate allele individuals only, when TRUE, heterozygous individuals are included assuming additive allele effects.
keep_outliers	When FALSE, marker group smoothing is performed to remove outliers.

Value

A comprehensive haplotyping S3 object (HapObject) for each provided epsilon value, needed for clustree_viz() and crosshap_viz().

crosshap documentation built on May 29, 2024, 1:13 a.m.