# Calculate Genomic Relatedness Matrix (GRM) for honeybees from Identical By Descent genomic data Level 0 function that returns Genomic Relatedness Matrix (GRM) for honeybees from Identical By Descent genomic data (tracked alleles since the founders) - see references on the background theory. ```r calcBeeGRMIbd(x) ``` ## Arguments - `x`: `matrix` of haplotypes/genomes with allele indicators for the founders coded as 1, 2, ... Haplotypes/genome are in rows and sites are in columns; no missing values are allowed (this is not checked!). Row names are essential (formated as ind_genome as returned by AlphaSimR IBD functions) to infer the individual and their ploidy (see examples)! ## Returns a list with a matrix of gametic relatedness coefficients (genome) and a matrix of individual relatedness coefficients (indiv) ## Examples ```r founderGenomes <- quickHaplo(nInd = 3, nChr = 1, segSites = 100) SP <- SimParamBee$new(founderGenomes) SP$setTrackRec(TRUE) SP$setTrackPed(isTrackPed = TRUE) basePop <- createVirginQueens(founderGenomes) drones <- createDrones(x = basePop[1], nInd = 1000) droneGroups <- pullDroneGroupsFromDCA(drones, n = 1, nDrones = nFathersPoisson) colony <- createColony(basePop[2]) colony <- cross(x = colony, drones = droneGroups[[1]]) colony <- buildUp(x = colony, nWorkers = 6, nDrones = 3) haploQ <- getQueenIbdHaplo(colony) haploW <- getWorkersIbdHaplo(colony) haploD <- getDronesIbdHaplo(colony) SP$pedigree haplo <- rbind(haploQ, haploW, haploD) GRMs <- calcBeeGRMIbd(x = haplo) # You can visualise this matrix with the image() functions from the "Matrix" package # Inspect the diagonal of the relationship matrix between individuals x <- diag(GRMs$indiv) hist(x) summary(x) # Inspect the off-diagonal of the relationship matrix between individuals x <- GRMs$indiv[lower.tri(x = GRMs$indiv, diag = FALSE)] hist(x) summary(x) ids <- getCasteId(colony) qI <- ids$queen wI <- sort(ids$workers) dI <- sort(ids$drones) qG <- c(t(outer(X = qI, Y = 1:2, FUN = paste, sep = "_"))) wG <- c(t(outer(X = wI, Y = 1:2, FUN = paste, sep = "_"))) dG <- paste(dI, 1, sep = "_") # Queen vs workers GRMs$genome[wG, qG] GRMs$indiv[wI, qI] # Queen vs drones GRMs$genome[dG, qG] GRMs$indiv[dI, qI] # Workers vs workers GRMs$genome[wG, wG] GRMs$indiv[wI, wI] # Workers vs drones GRMs$genome[dG, wG] GRMs$indiv[dI, wI] ``` ## References Grossman and Eisen (1989) Inbreeding, coancestry, and covariance between relatives for X-chromosomal loci. The Journal of Heredity, tools:::Rd_expr_doi("10.1093/oxfordjournals.jhered.a110812") Fernando and Grossman (1989) Covariance between relatives for X-chromosomal loci in a population in disequilibrium. Theoretical and Applied Genetics, tools:::Rd_expr_doi("10.1007/bf00305821") Fernando and Grossman (1990) Genetic evaluation with autosomal and X-chromosomal inheritance. Theoretical and Applied Genetics, tools:::Rd_expr_doi("10.1007/bf00224018") Van Arendonk, Tier, and Kinghorn (1994) Use of multiple genetic markers in prediction of breeding values. Genetics, tools:::Rd_expr_doi("10.1093/genetics/137.1.319") Hill and Weir (2011) Variation in actual relationship as a consequence of Mendelian sampling and linkage. Genetics Research, tools:::Rd_expr_doi("10.1017/s0016672310000480")

calcBeeGRMIbd function