#
(a_vector <- sample(0:10, 100, TRUE))
threshrank(a_vector, 5, keep0s=TRUE)
data(GlobalPatterns)
GP <- GlobalPatterns
## These three approaches result in identical otu_table
(x1 <- transform_sample_counts( otu_table(GP), threshrankfun(500)) )
(x2 <- otu_table(apply(otu_table(GP), 2, threshrankfun(500)), taxa_are_rows(GP)) )
identical(x1, x2)
(x3 <- otu_table(apply(otu_table(GP), 2, threshrank, thresh=500), taxa_are_rows(GP)) )
identical(x1, x3)
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