plot_tree from phyloseq missing branches names

[njbayonav]

Hey all,

I have a dataset that is a subset from the original qiime output. What I did was:

1: Filter those OTUs that I am interested in from the OTU table using qiime:
filter_taxa_from_otu_table.py -i ITS1.biom -o Hymenochaetaceae_ITS1.biom -p f__Hymenochaetaceae

2: Then create a new fasta file that only had sequences from those IDs from the new OTU table:
filter_fasta.py -f rep_set.fna -o Hymenochaetaceae_ITS1.fna -b Hymenochaetaceae_ITS1.biom

3: Then align this fasta file and make the tree
align_seqs.py -i Hymenochaetaceae_ITS1.fna -m muscle -o Hymenochaetaceae_ITS1/
make_phylogeny.py -i Hymenochaetaceae_ITS1/Hymenochaetaceae_ITS1_aligned.fasta -o Hymenochaetaceae_ITS1_phylo.tre

4. Then import the biom and the tree file in R using phyloseq and plot the tree
   biom="Hymenochaetaceae_ITS1.biom" tree="Hymenochaetaceae_ITS1_phylo.tre" biom=import_biom(biom,treefilename = tree, parseFunction=parse_taxonomy_default) tree=plot_tree(biom, nodelabf=nodeplotblank, ladderize="left", label.tips = "sample_Sample", title = "Hymenochaetaceae_ITS1",text.size = 3, color="Rank7")
   And finally, as you can see in the figure, my problem is that I get the tree plotted but not all branches has names on them. I guess those might be low abundant? But I am not totally sure what is happening.
   

I will appreciate any info!
Natalia

[njbayonav]

I just created a table with the counts of reads of each species within each sample.
merged = merge_samples(biom, "Sample") genfac = factor(tax_table(merged)[, "Rank7"]) gentab = apply(otu_table(merged), MARGIN = 1, function(x) { tapply(x, INDEX = genfac, FUN = sum, na.rm = TRUE, simplify = TRUE) }) gentab

In the table you will find:
-In purple, samples with no hits and no labels in the tree
-In yellow, samples with low abundance but with labels in the tree (3004T1)
-In orange, sample with hits, from low abundant to high abundant, but no labels in the tree.
-In blue, sample with high number of hits and label in the tree.

Then, I have more questions. I don't understand:

1. How samples without hits passed any of these two filtered explained above: filter_taxa_from_otu_table.py or filter_fasta.py.
2. Why some branches are labeled even if they have low absolute abundance? And some others are not, even if they have high abundance? What was the criterion?

[njbayonav]

I noticed that the sequences corresponded to reference sequences that were not in my dataset so I filtered those out.