t1 <- 1:10; names(t1)<-paste("t", 1:10, sep="")
rm_outlierf(0.15)(t1)
## Use simulated abundance matrix
set.seed(711)
testOTU <- otu_table(matrix(sample(1:50, 25, replace=TRUE), 5, 5), taxa_are_rows=FALSE)
taxa_sums(testOTU)
f1 <- filterfun_sample(rm_outlierf(0.1))
(wh1 <- genefilter_sample(testOTU, f1, A=1))
wh2 <- c(TRUE, TRUE, TRUE, FALSE, FALSE)
prune_taxa(wh1, testOTU)
prune_taxa(wh2, testOTU)
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