Description Usage Arguments Value Examples
CO
is an internal function used in count_CO
to count
crossovers. CO
is provided in case there is a use case for
the user. We used this function for QA and it can be used for
estimates of crossover assurance.
1 |
indata |
this is a binary coded genotype data frame from a genotypeR object (see example below). |
naive |
this takes 2 values: 1) FALSE (default) returns list with COs distributed by marker distance, and 2) TRUE returns a list with COs without regard to marker distance (i.e., at the final non-missing data point in a string of missing genotypes) |
list of COs counted per individual
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | library(doBy)
data(genotypes_data)
data(markers)
## genotype table
marker_names <- make_marker_names(markers)
GT_table <- Ref_Alt_Table(marker_names)
## remove those markers that did not work
genotypes_data_filtered <- genotypes_data[,c(1, 2, grep("TRUE",
colnames(genotypes_data)%in%GT_table$marker_names))]
warnings_out2NA <- initialize_genotypeR_data(seq_data = genotypes_data_filtered,
genotype_table = GT_table, output = "warnings2NA")
binary_coding_genotypes <- binary_coding(warnings_out2NA, genotype_table = GT_table)
chr2 <- subsetChromosome(binary_coding_genotypes, chromosome="chr2")
to_count_CO <- binary_genotypes(chr2)
counted_per_individuals <- lapply(splitBy(~SAMPLE_NAME+WELL, data=to_count_CO), CO)
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