clustering_kos<-function(databiomKO, estadio){
y <- read_biom("ko_predictions.biom")
otumaty = as(biom_data(y), "matrix")
OTUy = otu_table(otumaty, taxa_are_rows=TRUE)
taxmaty = as.matrix(observation_metadata(y), rownames.force=TRUE)
TAXy = tax_table(taxmaty)
path_1 = phyloseq(OTUy, TAXy, map)
wh0Ko = genefilter_sample(path_1, filterfun_sample(function(x) x > 5), A=0.5*nsamples(path_1))
GP1Ko = prune_taxa(wh0Ko, path_1)
GP1Ko = transform_sample_counts(GP1Ko, function(x) 1E6 * x/sum(x))
kO1 <- subset_samples(GP1Ko, SampleType == "Larvae")
pdf("KOclustering.pdf", width=10, height=10)
orduKo = ordinate(kO1, "PCoA", "bray")
pKo = plot_ordination(kO1, orduKo, color="Host")
pKo = pKo + geom_point(size=3, alpha=0.75)
pKo = pKo + scale_colour_brewer(type="qual", palette="Set1")
pKo + ggtitle("MDS/PCoA on Bray distance, KOs")
dev.off()
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.