dfilter | R Documentation |
Simplifies the process of eliminating subpopulations with low sample sizes.
dfilter(data, minsample)
data |
Matrix containing genotype data with individuals as rows and loci as columns. Genotypes should be coded as 0 (homozygous), 1 (heterozygous), or 2 (homozygous). Rownames must be subpopulation names and column names should be marker names. |
minsample |
An integer representing the smallest number of individuals a subpopulation must contain to be included in analysis. |
filtered_data The original dataset minus the subpopulations that fail to meet the sample size threshold.
test <- matrix(round(runif(400,1,2)), nrow = 100) rownames(test) <- c(rep(c('A','B','C'),each=25), rep(c('D','E'), each=5), rep('F', 15)) dim(test) #The 'D' and 'E' subpopulations have only five members each and should be removed filtered_test <- dfilter(test,12) dim(filtered_test) # New dataset is reduced by 10 rows (five for 'D' and five for 'E')
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