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Count opposing homozygous SNPs between pairs of individuals

CountOH.Rd

Quick identification of likely parents, as the number of opposing homozygous (OH) SNPs is expected to be zero for parent- offspring pairs in absence of genotyping errors, and greater than zero for all other pairs.

Usage

CountOH(x = NULL, ID2 = NULL, GenoM = NULL, max_OH = -1, quiet = FALSE)

Arguments

x

Either a matrix, dataframe or similar where the first two columns are individual IDs, or a vector with IDs. In the second case, you may provide ID2, and the output will be an ID1 x ID2 matrix; else the output will be an ID1 x ID1 matrix. Non-genotyped individuals are included in the results with all NA's, and a warning.

ID2

optional second vector with IDs

GenoM

numeric matrix with genotype data: One row per individual, one column per SNP, coded as 0, 1, 2, missing values as a negative number or NA. Row names must be individual IDs, column names are ignored. You can reformat data with GenoConvert, or use other packages to get it into a genlight object and then use as.matrix.

max_OH

stop counting OH's for a pair if this value is reached, to reduce computation time. Ignored if negative value or equal to total number of SNPs.

quiet

suppress messages

Details

Counting the number of opposing homozygous (OH) SNPs is much faster than calculating likelihoods, and does not rely on an estimated genotyping error rate. It can therefore be useful during quality control, or to help figure out problems when assignment rate with sequoia is lower than expected.

See also

CalcPairLL to calculate likelihoods for pairs, CalcOHLLR to calculate OH for a pedigree, CalcMaxMismatch for calculation of the maximum OH used by sequoia to filter potential parent-offspring pairs.

Examples

offspring_ids <- with(LH_HSg5, ID[BirthYear==2001])
candidate_father_ids <- with(LH_HSg5, ID[BirthYear==2000 & Sex==2])

OH_matrix <- CountOH(offspring_ids, candidate_father_ids, GenoM=Geno_HSg5)
#> ℹ Some IDs are not among rownames of GenoM

hist(c(OH_matrix), breaks=c(0:40)-.5)

# with high quality SNP data, there is often a clear separation in OH counts
# between parent-offspring pairs (here: OH<3) and others (here: OH>4).
# BUT: non-PO close relatives may have very low OH counts by chance,
# and true PO pairs may have fairly high OH counts due to genotyping errors.