HOLOVINI-PILOTE

As part of the HOLOVINI project funded by the HOLOFLUX metaprogramme, we aim to identify microbial flows between the environment, insects, vines and winery. This is a pilot experiment to validate experimental methodology (nets, metabarcoding primers, DNA extraction methods…).

closed
collaboration
Author
Affiliation

Olivier Rué

Migale bioinformatics facility

Published

June 13, 2024

Modified

October 31, 2024

Note

This document is a report of the analyses performed. You will find all the code used to analyze these data. The version of the tools (maybe in code chunks) and their references are indicated, for questions of reproducibility.

Aim of the project

As part of the HOLOVINI project funded by the HOLOFLUX metaprogramme, we aim to identify microbial flows between the environment, insects, vines and winery.

Partners

  • Olivier Rué - Migale bioinformatics facility - BioInfomics - INRAE
  • Jean-Luc Legras - SPO - INRAE

Deliverables

Deliverables agreed at the preliminary meeting (Table 1).

Table 1: Deliverables
  Definition Status
1 HTML report ✔️
2 RDS files ✔️
3 Taxonomies and abundances for a manual curation ✔️

Data management

Important

All data is managed by the migale facility for the duration of the project. Once the project is over, the Migale facility does not keep your data. We will provide you with the raw data and associated metadata that will be deposited on public repositories before the results are used. We can guide you in the submission process. We will then decide which files to keep, knowing that this report will also be provided to you and that the analyses can be replayed if needed.

Raw data

Raw data were available with those of the project LTMCBW2, available on the front server. A copy was sent to the abaca server.

mkdir /home/orue/work/PROJECTS/HOLOVINI/
cd /home/orue/work/PROJECTS/HOLOVINI/
mkdir -p 16S/RAW_DATA/ ITS/RAW_DATA/
cd 16S
cp ../../LTMCBW2/RAW_DATA_READY/PAUL/*16S* .
rename 's/-16S_S\d+_/_/' *.fastq.gz
mkdir RAW_DATA/
mv *.fastq.gz RAW_DATA/
cp ../../LTMCBW2/RAW_DATA_READY/16S/MockBW-16S-* 
mv MockBW-16S-D2_R2.fastq.gz RAW_DATA/MockBW-D2_R2.fastq.gz
mv MockBW-16S-D2_R1.fastq.gz RAW_DATA/MockBW-D2_R1.fastq.gz
mv MockBW-16S-G4_R2.fastq.gz RAW_DATA/MockBW-G4_R2.fastq.gz
mv MockBW-16S-G4_R1.fastq.gz RAW_DATA/MockBW-G4_R1.fastq.gz
for i in RAW_DATA/*_R1.fastq.gz ; do echo $i ; done |wc -l
35 # 16S samples

cd ../ITS
cp ../../LTMCBW2/RAW_DATA_READY/PAUL/*ITS* .
rename 's/-ITS_S\d+_/_/' *.fastq.gz
mv *.fastq.gz RAW_DATA/
cp ../../LTMCBW2/RAW_DATA_READY/PAUL/MockY-Cave_S92_R* .
renamed 'MockY-Cave_S92_R2.fastq.gz' -> 'RAW_DATA/MockY-Cave_R2.fastq.gz'
mv MockY-Cave_S92_R1.fastq.gz RAW_DATA/MockY-Cave_R1.fastq.gz
mv MockY-Cave_S92_R2.fastq.gz RAW_DATA/MockY-Cave_R2.fastq.gz
for i in RAW_DATA/*_R1.fastq.gz ; do echo $i ; done |wc -l
35 # ITS samples

cd ../
scp ITS/RAW_DATA/*.fastq.gz orue@abaca.maiage.inrae.fr:/backup/partage/migale/HOLOVINI/ITS/
scp 16S/RAW_DATA/*.fastq.gz orue@abaca.maiage.inrae.fr:/backup/partage/migale/HOLOVINI/16S/

Quality control

seqkit [1] was used to get informations from FASTQ files.

# seqkit
cd /home/orue/work/PROJECTS/HOLOVINI/16S 
qsub -cwd -V -N seqkit -pe thread 4 -R y -b y "conda activate seqkit-2.0.0 && seqkit stats /home/orue/work/PROJECTS/HOLOVINI/16S/RAW_DATA/*.fastq.gz -j 4 > raw_data.infos && conda deactivate"

We can plot and display the number of reads to see if enough reads are present and if samples are homogeneous.

raw_data %>% select(sample, num_seqs, sum_len, min_len, avg_len, max_len) %>% datatable()

FastQC [2] is a program designed to spot potential problems in high througput sequencing datasets. It runs a set of analyses on one or more raw sequence files in fastq or bam format and produces a report which summarises the results. MultiQC [3] aggregates results from bioinformatics analyses across many samples into a single report.

cd /home/orue/work/PROJECTS/HOLOVINI/16S/
mkdir FASTQC LOGS
for i in /home/orue/work/PROJECTS/HOLOVINI/16S/RAW_DATA/*.fastq.gz ; do echo "conda activate fastqc-0.11.9 && fastqc $i -o FASTQC && conda deactivate" >> fastqc.sh ; done
qarray -cwd -V -N fastqc -o LOGS -e LOGS fastqc.sh
qsub -cwd -V -N multiqc -o LOGS -e LOGS -b y "conda activate multiqc-1.11 && multiqc FASTQC -o MULTIQC && conda deactivate"

The MultiQC report shows expected metrics for Illumina Miseq sequencing data.

Note

The quality control is good enough to go further.

# seqkit
cd /home/orue/work/PROJECTS/HOLOVINI/ITS
qsub -cwd -V -N seqkit -pe thread 4 -R y -b y "conda activate seqkit-2.0.0 && seqkit stats /home/orue/work/PROJECTS/HOLOVINI/ITS/RAW_DATA/*.fastq.gz -j 4 > raw_data.infos && conda deactivate"

We can plot and display the number of reads to see if enough reads are present and if samples are homogeneous.

raw_data %>% select(sample, num_seqs, sum_len, min_len, avg_len, max_len) %>% datatable()

FastQC [2] is a program designed to spot potential problems in high througput sequencing datasets. It runs a set of analyses on one or more raw sequence files in fastq or bam format and produces a report which summarises the results. MultiQC [3] aggregates results from bioinformatics analyses across many samples into a single report.

cd /home/orue/work/PROJECTS/HOLOVINI/ITS/
mkdir FASTQC LOGS
for i in /home/orue/work/PROJECTS/HOLOVINI/ITS/RAW_DATA/*.fastq.gz ; do echo "conda activate fastqc-0.11.9 && fastqc $i -o FASTQC && conda deactivate" >> fastqc.sh ; done
qarray -cwd -V -N fastqc -o LOGS -e LOGS fastqc.sh
qsub -cwd -V -N multiqc -o LOGS -e LOGS -b y "conda activate multiqc-1.11 && multiqc FASTQC -o MULTIQC && conda deactivate"

The MultiQC report shows expected metrics for Illumina Miseq sequencing data.

Note

The quality control is good enough to go further.

Bioinformatics

We used FROGS v.5.0.0 [4], [5] to build amplicon sequence variants (ASVs) from raw reads.

The first tool, called denoising allows to clean reads. From FASTQ files, reads with N were first discarded. Then, reads were denoised with dada2 [6], R1 and R2 reads were overlaped (if possible, otherwise we keep R1 and R2 for ITS) with pear [7], then primers were removed with cutadapt [8], remaining sequences were filtered on length and finally dereplicated.

cd /home/orue/work/PROJECTS/HOLOVINI/16S
cd RAW_DATA/
tar zcvf Holovini_16S.tar.gz *.fastq.gz
cd ../
mkdir FROGS5
cd FROGS5
conda activate frogs-5.0.0
denoising.py illumina --min-amplicon-size 300 --max-amplicon-size 590 --merge-software pear --five-prim-primer TACGGRAGGCAGCAG --three-prim-primer GGATTAGATACCCBDGTAGTC --R1-size 300 --R2-size 300 --nb-cpus 16 --output-fasta clusters.fasta --output-biom clusters.biom --html denoising.html --log-file denoising.log --process dada2 --input-archive ../RAW_DATA/Holovini_16S.tar.gz
remove_chimera.py --input-biom clusters.biom --input-fasta clusters.fasta --html remove_chimera.html --log-file remove_chimera.log --nb-cpus 16

20% of sequences detected as chimera and removed

cluster_filters.py --input-fasta remove_chimera.fasta --input-biom remove_chimera_abundance.biom --nb-cpus 16 --contaminant /db/outils/FROGS/contaminants/phi.fa --min-abundance 0.00005 --output-fasta filters.fasta --log-file filters.log --html cluster_filters.html
taxonomic_affiliation.py --input-biom cluster_filters_abundance.biom --input-fasta filters.fasta --nb-cpus 16 --reference /db/outils/FROGS/assignation/silva_138.1_16S_pintail100/silva_138.1_16S_pintail100.fasta --log-file taxonomic_affiliation.log
tree.py --input-biom affiliation_abundance.biom --html tree.html --output-tree tree.nwk --log-file tree.log --input-fasta filters.fasta
cd /home/orue/work/PROJECTS/HOLOVINI/ITS
cd RAW_DATA/
tar zcvf Holovini_ITS.tar.gz *.fastq.gz
cd ../
mkdir FROGS5
cd FROGS5
conda activate frogs-5.0.0
denoising.py illumina --min-amplicon-size 50 --max-amplicon-size 1000 --merge-software pear --five-prim-primer GCATCGATGAAGAACGCAGC --three-prim-primer GCAWAWCAAWAAGCGGAGGA --R1-size 300 --R2-size 300  --nb-cpus 16 --output-fasta clusters.fasta --output-biom clusters.biom --html denoising.html  --log-file preprocess.log --process dada2 --input-archive ../RAW_DATA/Holovini_ITS.tar.gz --keep-unmerged
remove_chimera.py --input-biom clusters.biom --input-fasta clusters.fasta --html remove_chimera.html --log-file remove_chimera.log --nb-cpus 16
cluster_filters.py --input-fasta remove_chimera.fasta --input-biom remove_chimera_abundance.biom --nb-cpus 16 --contaminant /db/outils/FROGS/contaminants/phi.fa --min-abundance 0.00005 --output-fasta filters.fasta --log-file filters.log --html cluster_filters.html
itsx.py --check-its-only --input-fasta filters.fasta --input-biom cluster_filters_abundance.biom --log-file itsx.log
taxonomic_affiliation.py --input-biom itsx_abundance.biom --input-fasta itsx.fasta --nb-cpus 16 --reference ~/work/PROJECTS/LEBANESEWHEATSOURDOUGH/ITS/UNITE_9.0_20221016_plus_METABARFOOD.fasta --log-file taxonomic_affiliation.log
tree.py --input-biom affiliation_abundance.biom --html tree.html --output-tree tree.nwk --log-file tree.log --input-fasta itsx.fasta

Biostatisctics

Phyloseq [9] is a R package dedicated to diversity analyses.

To create a phyloseq object, we need the BIOM file, the metadata file and eventually a tree file.

library(phyloseq)
library(phyloseq.extended)
library(Biostrings)
biomfile <- "data/affiliation_16S.biom"
frogs16S <- import_frogs(biomfile, taxMethod = "blast")
metadata <- read.table("data/metadata_16S.txt", row.names = 1, header = TRUE, sep = "\t", stringsAsFactors = FALSE)
phy_tree(frogs16S) <- read_tree("data/tree_16S.nwk")
sample_data(frogs16S) <- metadata
frogs16S
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 1250 taxa and 35 samples ]
sample_data() Sample Data:       [ 35 samples by 3 sample variables ]
tax_table()   Taxonomy Table:    [ 1250 taxa by 7 taxonomic ranks ]
phy_tree()    Phylogenetic Tree: [ 1250 tips and 1249 internal nodes ]
fasta_file <- "data/asv_16S.fasta"
sequences_16S <- readDNAStringSet(fasta_file)
#taxa_names(frogs16S) <- unlist(as.character(sequences_16S))

clusters_in_frogs16S <- taxa_names(frogs16S)
matched_sequences <- sequences_16S[match(clusters_in_frogs16S, names(sequences_16S))]

# Check correspondance
if (any(is.na(matched_sequences))) {
  stop("Some ASVs are not in the FASTA file! Please check...")
}
taxa_names(frogs16S) <- as.character(matched_sequences)

Remove Mitochondria and Chloroplast

Let look at the proportion of Mitochondria and Chloroplast…

frogs16S_order <- tax_glom(frogs16S, taxrank = "Order") # Agglomerate at Order level to assess chloroplast proportion

# Calculate relative abundance
frogs16S_order.prop <- transform_sample_counts(frogs16S_order, function(x) x / sum(x) )
# Subset object to only Chloroplast
frogs16S_order.prop.chhloro <- subset_taxa(frogs16S_order.prop, Order == "Chloroplast")
tchloro <- otu_table(frogs16S_order.prop.chhloro) %>% as.data.frame()
rownames(tchloro) <- c("Chloroplast")

frogs16S_family <- tax_glom(frogs16S, taxrank = "Family")
frogs16S_family.prop <- transform_sample_counts(frogs16S_family, function(x) x / sum(x) )
frogs16S_family.prop.mito <- subset_taxa(frogs16S_family.prop, Family == "Mitochondria")
tmito <- otu_table(frogs16S_family.prop.mito) %>% as.data.frame()
rownames(tmito) <- c("Mitochondria")
library(reactable)
reactable(rbind(tchloro, tmito), defaultColDef = colDef(format = colFormat(digits = 2)))

Then, I remove Mitochondria and Chloroplast of the dataset:

frogs16S <- frogs16S %>% subset_taxa(Order != "Chloroplast" & Family != "Mitochondria")
frogs16S
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 1088 taxa and 35 samples ]
sample_data() Sample Data:       [ 35 samples by 3 sample variables ]
tax_table()   Taxonomy Table:    [ 1088 taxa by 7 taxonomic ranks ]
phy_tree()    Phylogenetic Tree: [ 1088 tips and 1087 internal nodes ]

Finally I save my phyloseq object in a RDS file:

saveRDS(frogs16S,file="html/frogs16S.rds")

Affiliations

taxonomy_table <- as.data.frame(tax_table(frogs16S))
clusters <- taxa_names(frogs16S)
abundances <- as.data.frame(otu_table(frogs16S))
abundance_global <- rowSums(abundances)
result_tibble <- taxonomy_table %>%
  rownames_to_column(var = "ASV") %>%  
  mutate(Abundance = abundance_global)     
result_tibble <- as_tibble(result_tibble)
result_tibble %>% datatable()
write.table(result_tibble, "html/16S_affiliations.txt", append=TRUE, quote = FALSE, row.names = FALSE, col.names = TRUE, sep = "\t" )

This table is downloadable at the end of this document.

Compositions

cat("\n")

To create a phyloseq object, we need the BIOM file, the metadata file and eventually a tree file.

library(phyloseq)
library(phyloseq.extended)
biomfile <- "data/affiliation_ITS.biom"
frogsITS <- import_frogs(biomfile, taxMethod = "blast")
phy_tree(frogsITS) <- read_tree("data/tree_ITS.nwk")
metadata <- read.table("data/metadata_ITS.txt", row.names = 1, header = TRUE, sep = "\t", stringsAsFactors = FALSE)
sample_data(frogsITS) <- metadata
frogsITS
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 649 taxa and 35 samples ]
sample_data() Sample Data:       [ 35 samples by 3 sample variables ]
tax_table()   Taxonomy Table:    [ 649 taxa by 7 taxonomic ranks ]
phy_tree()    Phylogenetic Tree: [ 649 tips and 648 internal nodes ]
fasta_file <- "data/asv_ITS.fasta"
sequences_ITS <- readDNAStringSet(fasta_file)

clusters_in_frogsITS <- taxa_names(frogsITS)
matched_sequences <- sequences_ITS[match(clusters_in_frogsITS, names(sequences_ITS))]

# Check correspondance
if (any(is.na(matched_sequences))) {
  stop("Some ASVs are not in the FASTA file! Please check...")
}
taxa_names(frogsITS) <- as.character(matched_sequences)

Some affiliations have to be changed, due to differences in some taxonomies (i.e. Pichia affiliated as Pichiaceae family vs. Saccharomycetaceae family)

change_complete_taxo <- function(t, taxo, sequence){
  
  taxolist <- unlist(strsplit(taxo, ";"))
  if(sequence %in% rownames(t)){
    t[sequence,"Kingdom"] <- taxolist[1]
    t[sequence,"Phylum"] <- taxolist[2]
    t[sequence,"Class"] <- taxolist[3]
    t[sequence,"Order"] <- taxolist[4]
    t[sequence,"Family"] <- taxolist[5]
    t[sequence,"Genus"] <- taxolist[6]
    t[sequence,"Species"] <- taxolist[7]  
  }
  return(t)
}

t <- phyloseq::tax_table(frogsITS)
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Pichiaceae;Pichia;Pichia_kluyveri","GAAATGCGATACCTAGTGTGAATTGCAGCCATCGTGAATCATCGAGTTCTTGAACGCACATTGCGCCCCATGGTATTCCATGGGGCATGCCTGTCTGAGCGTCGTTTCCTTCTTGCGCAAGCAGAGTTGAGAACAGGCTATGCCTTTTTCGAAATGGAACGTCGTGGACGAAGTGAACTAAATTATTGGAACGCTTTGGCCGCCGAACTTTTAACTAAGCTCGACCTCAGATCAGGTAGGAATACCCGCTGAACTTAA")
phyloseq::tax_table(frogsITS) <- t

Affiliations

taxonomy_table <- as.data.frame(tax_table(frogsITS))
clusters <- taxa_names(frogsITS)
abundances <- as.data.frame(otu_table(frogsITS))
abundance_global <- rowSums(abundances)
result_tibble <- taxonomy_table %>%
  rownames_to_column(var = "ASV") %>%  
  mutate(Abundance = abundance_global)     
result_tibble <- as_tibble(result_tibble)
result_tibble %>% datatable()

Modifications of some affiliations

t <- phyloseq::tax_table(frogsITS)

change_complete_taxo <- function(t, taxo, sequence){
  
  taxolist <- unlist(strsplit(taxo, ";"))
  if(sequence %in% rownames(t)){
    t[sequence,"Kingdom"] <- taxolist[1]
    t[sequence,"Phylum"] <- taxolist[2]
    t[sequence,"Class"] <- taxolist[3]
    t[sequence,"Order"] <- taxolist[4]
    t[sequence,"Family"] <- taxolist[5]
    t[sequence,"Genus"] <- taxolist[6]
    t[sequence,"Species"] <- taxolist[7]  
  }
  return(t)
}

t <- change_complete_taxo(t,"Fungi;Basidiomycota;Agaricostilbomycetes;Agaricostilbales;Kondoaceae;Kondoa;Kondoa_aeria","GAAATGCGATACGTAATGTGAATTGCAGAACTCAGTGAATCATCGAATTTTTGAACGCACCTTGCGCTCTTTAGTTATTCTGAAGAGCATGCTTGTTTGAGTGTCGCGAACCTCTCAACCCCGCCCAAGGCTTAATTGACTTGCGGTTGTTTGGGCTTGGATCATGGTCTCTTGTCGTTACCTTCGGGTTTGGACTGGACTGAAATACAACAAGTTGAATGGTTTCCATTTGCAGCTTGACCTGATGTTGTAAACTACTCATCGGGGATGCAATGAAGCTAAAGGAACTTTAACAGAACCCCTTAAATGGTACCTAGTACATTTATGACCTCAAATCAAGTAGGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Basidiomycota;Agaricomycetes;Russulales;Peniophoraceae;Entomocorticium;Entomocorticium_sp","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACCTTGCGCCCCTTGGCATTCCGAGGGGCACGCCTGTTTGAGTGTCGTGAACTCCTCCACCCTCTACCTTTTTCGGAAGGCACTGGGCTGGGATTTGGGAGCTTGCGGGTCCCTGGCCGATCCGCTCTCCTTGAATACATTAGCGAAGCCCTTGCGGCCTTGGTGTGATAGTCATCTACGCCTTGGCTTAGCGAACATATGGGAATCGCTTCCAACCGTCTCGCAAGAGACAATCACTACCAACTTGACCTCAAATCAGGCGGGACTACCCGCTGAACTTAA")

t <- change_complete_taxo(t,"Fungi;Basidiomycota;Agaricomycetes;Thelephorales;Thelephoraceae;Tomentella;Tomentella_tedersooi","TAAATGTGACAATTAATGTGACTTGCAGAGTACGTGAATCATCAAGTATTTGAATGCACATTGCACTTTCTGTTCAAGAAAGTATACCTGTTTGAGTACCATATTCTTTTCCCTTTAATGGAAACTTGTGTCATCCGTTGCGCTTTTAGCGGCGACGGCGATACAAATTAAAGAGTCCAACTCGAGACGTAAAAACATTGCAAAATGATTGAACGTTGCGCGTTGCTTTACTACAACTTTTTTGAATTGATCTCAAATCAGGCAGGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Basidiomycota;Agaricomycetes;Thelephorales;Thelephoraceae;Tomentella;Tomentella_tedersooi","TAAATGTGACAATTAATGTGACTTGCAGAGTACGTGAATCATCAAGTATTTGAATGCACATTGCACTTTCTGTTCAAGAAAGTATACCTGTTTGAGTACCATATTCTTTTCCCTTTAATGGAAACTTGTGTCATCCGTTGCGCTTCTAGCGGCGACGGCGATACAAATTAAAGAGTCCAACTCGAGACGTAAAAACATTGCAAAATGATTGAACGTTGTGCGTTGCTTTACTACAACTTTTTTGAATTGATCTCAAATCAGGCAGGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Mortierellomycota;Mortierellomycetes;Mortierellales;Mortierellaceae;Mortierella;Mortierella_alpina","GAAATGCGATACGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCATATTGCGCTCTCTGGTATTCCGGAGAGCATGCTTGTTTGAGTATCAGTAAACACCTCAACTCCCTTTTCTTTTTTGAAATTGGAGCTGGACTTGAGTGATCCCAACGCTTTCTTCCAAGAAAGTGGCGGGTTGCTTGAAATGCAGGTGCAGCTGAACTTTTCTCTGAGCTATAAGCATATCTATTTAGTCTGCCTAAAAAACAGATTATTACCTTTGCTGCAGCTAACATAAAGGAGACTAGTTCTTGTGCTGACTGATGCAGGATTCACAGAGACAGCTTCGGCTGACTTTGTAAACTCGATCTCAAATCAAGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Sordariomycetes;Hypocreales;Nectriaceae;Fusarium;Fusarium_sp","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCGCCAGTATTCTGGCGGGCATGCCTGTTCGAGCGTCATTTCAACCCTCAAGCCCCCGGGTTTGGTGTTGGGGATCGGGCTGTACTCCAGCCCGGCCCCGAAATCTAGTGGCGGTCTCGCTGCAGCCTCCATTGCGTAGTAGCTAACACCTCGCAACTGGAACGCGGCGCGGCCAAGCCGTTAAACCCCCAACTTCTGAATGTTGACCTCGGATCAGGTAGGAATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Sordariomycetes;Trichosphaeriales;Trichosphaeriaceae;Nigrospora;Nigrospora_sphaerica","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCATTAGTATTCTAGTGGGCATGCCTGTTCGAGCGTCATTTCAACCCCTAAGCACAGCTTATTGTTGGGAACCTACGGCTTCGTAGTTCCTCAAAGACATTGGCGGAGTGGCAGTGGTCCTCTGAGCGTAGTAATCTTTTATCTCGCTTCTGTTAGGTGCTGCCCCCCCGGCCGTAAAACCCCCAATTTTTTCTGGTTGACCTCGGATCAGGTAGGAATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Eurotiomycetes;Chaetothyriales;Trichomeriaceae;Knufia;Knufia_sp","GAAATGCGATAAGTAATGCGAATTGCAGAATTTCCGTGAGTCATCGAATCTTTGAACGCACATTGCGCCCACTGGTATTCCGGTGGGCATGCCTGTTCGAGCGTCATTATCCTCCCTCAAACCCCGGGTTTGGTGTTGGACCGAAGTTGTGTGAACAACTGGTCTAAAAGACAATGACGGCGTCCGTGGGACCCTCGGTGCAACGAGCTTTTAGGAGCACGCGCCGAGTTGCAAGGACCTTCCGGGCCGGTCTCCTTTTACTATTTTACAAGGTTGACCTCGGATCAGGTAGGAATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Basidiomycota;Tremellomycetes;Tremellales;Bulleribasidiaceae;Vishniacozyma;Vishniacozyma_dimennae","GAAATGCGATAAGTAGTGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCTCGGTATCCCGGGGGGCATGCCTGTTCGAGCGTCATTTCTACCACTCAAGCACAGCTTGGTATTGGGTGTCGTTGCTTTTCTAGCCAACGTGCCTTAAATGTAGACGGCAGCAAGCACCAGTTCCGAGCGTAGCAGAAAACTCGCTTTAGGGGCTTTGGGGCATTGCTAACCGCATAAGCTTTTTTATAAGTTTGACCTCGGATCAGGCAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTCCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCTTGGTATTCCGAGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCTTTGGTATTCCAAAGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCTTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAAGTAATGTGAATTGCAGAATTCCGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAACTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTCCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAACTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATACGTAGTGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGACCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATACGTAGTGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Cladosporiales;Cladosporiaceae;Cladosporium;Multi-affiliation","GAAATGCGATAAGTAGTGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCACCACTCAAGCCTCGCTTGGTATTGGGCAACGCGGTCCGCCGCGTGCCTCAAATCGTCCGGCTGGGTCTTCTGTCCCCTAAGCGTTGTGGAAACTATTCGCTAAAGGGTGTTCGGGAGGCTACGCCGTAAAACAACCCCATTTCTAAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Pleosporales;Torulaceae;Torula;Torula_ligniperda","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCTTGGTATTCCGAGGGGCATGCCTGTTCGAGCGTCATTTCAACCCCTCAAGCTTAGCTTGGTGTTGGGCTGCGCCAGCGTTGCTGGCGGGCCTTAAAATCAGTGGCGGTGCCGTTTGGGCTCCAAGCGTAGTAGCATCTCTCGCTCTGGAGACCCGGCGGTTGCTTGCCAGACAATCACTAAAAAAACAAAGGTTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Leotiomycetes;Helotiales;Sclerotiniaceae;Stromatinia;Multi-affiliation","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCTTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTTCAACCCTCAAGCTCAGCTTGGTATTGGGCCTCCGCCGGTCACACGGCGGGCCTTAAAGTCAGTGGCGGCGCCGTTGGGTCCTGAACGTAGTAACATACATCTCGTTACAGGGTCCCCGCGTGCTTCTGCCATTAAACCCCCAATTTCTATGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Leotiomycetes;Helotiales;Ploettnerulaceae;Cadophora;Cadophora_luteo-olivacea","GAAATGCGATAAGTAATGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCTCTGGTATTCCGGGGGGCATGCCTGTTCGAGCGTCATTATAACCACTCAAGCTCTCGCTTGGTATTGGGGTTCGCGGTTTCGCGGCTCCTAAAATCAGTGGCGGTGCCTGTCGGCTCTACGCGTAGTAATACTCCTCGCGTCTGGGTCCGGTAGGTCTACTTGCCAGCAACCCCCAATTTTTACAGGTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Pleosporales;Sporormiaceae;Preussia;Multi-affiliation","GAAATGCGATAAGTAGTGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCTTTGGTATTCCTTAGGGCATGCCTGTTCGAGCGTCATTTAAACCTTCAAGCTCAGCTTGGTGTTGGGTGACTGTCCGCTTCACTGCGGACTCGCCTCAAAATTATTGGCGGCCGGTACATTGGCTTCGAGCGCAGCAGAAACGCGAACTCGGGCCCGTCGTATTGGCTCCCAGAAGCTATCTTCACAATTTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Pleosporales;Sporormiaceae;Sporormiella;Sporormiella_sp","GAAATGCGATAAGTAGTGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCTTTGGTATTCCTTAGGGCATGCCTGTTCGAGCGTCATTTAAACCTTCAAGCTAAGCTTGGTGTTGGGTGACTGTCCGCTTCACGGCGGACTCGCCTCAAAATTATTGGCGGCCGGTACATTGGCTTCGAGCGCAGCAGAAACGCGAACTCGGGCCCGTCGTATTGGCTCCCAGAAGCTATCTTCACAATTTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Pleosporales;Lophiostomataceae;Lophiostoma;Lophiostoma_sp","GAAATGCGATAAGTAGTGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCTTTGGTATTCCTTAGGGCATGCCTGTTCGAGCGTCATTTACAAATTCAAGCTCAGCTTGGTGATGGGTGTCTGTCCCGCCTTTGCGTGTGGACTCGCCTCAAATGCAGTTGGCAGCTTGTTCCTCGGCTCTAAACGCAGCAGATTTGCGTCGAGCGTCGTGCGGACGGGCTCTCCAGTAAGCAAACCCCACAAATTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Dothideomycetes;Pleosporales;Cucurbitariaceae;Pyrenochaeta;Pyrenochaeta_sp","GAAATGCGATAAGTAGTGTGAATTGCAGAATTCAGTGAATCATCGAATCTTTGAACGCACATTGCGCCCCTTGGTATTCCATGGGGCATGCCTGTTCGAGCGTCATTTGTACCCTCCAGCCCTGCTGGGTGTTGGGCGTTTGTTCCGCCGCGTGCGTGAACTCGCCTCAAATACATTGGCAGCCCGCCGTCCCGTGTGGGAGCGCAGCACATTTTGCGCTCTCCGCTGCAGACGGCGGCATCCACAAGTCTACACCTTTACGCTTGACCTCGGATCAGGTAGGGATACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Saccharomycodaceae;Hanseniaspora;Hanseniaspora_pseudoguilliermondii","GAATTGCGATAAGTAATGTGAATTGCAGATACTCGTGAATCATTGAATTTTTGAACGCACATTGCGCCCTTGAGCATTCTCAAGGGCATGCCTGTTTGAGCGTCATTTCCTTCTCAAAAGATAATTTATTATTTTTTGGTTGTGGGCGATACTCAGGGTTAGCTTGAAATTGGAGACTGTTTCAGTCTTTTTTAATTCAACACTTAGCTTCTTTGGAGACGCTGTTCTCGCTGTGATGTATTTATGGATTTATTCGTTTTACTTTACAAGGGAAATGGTAACGTACCTTAGGCAAAGGGTTGCTTTTAATATTCATCAAGTTTGACCTCAAATCAGGTAGGATTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Saccharomycetaceae;Pichia;Pichia_kluyveri","GAAATGCGATACCTAGTGTGAATTGCAGCCATCGTGAATCATCGAGTTCTTGAACGCACATTGCGCCCCATGGTATTCCATGGGGCATGCCTGTCTGAGCGTCGTTTCCTTCTTGCGCAAGCAGAGTTGAGAACAGGCTATGCCTTTTTCGAAATGGAACGTCGTGGACGAAGTGAACTAAACTTTTTAGCCCGCTTTGCCGGCCGAACTTTTTACTAAGCTCGACCTCAGATCAGGTAGGAATACCCGCTGAACTAAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_sp","GAATTGCGATAAGTAATGTGAATTGCAGATACTCGTGAATCATTGAATTTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCGACGGCGCTAGAATAAGTTTTAGCCCCAGCCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATTTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCAGCCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCAGTCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATCCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTAGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","CGACGAGCATAACAATAAGCGGAGGAACCCNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNTGGCATCGATGAAGAACGCAGCGAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCATAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTCTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAGTCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCATAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTCTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATTTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCATAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTCTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAGTCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTCTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTCTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAGCCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCATTCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAGTCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCAGCCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCCGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCAGCCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")
t <- change_complete_taxo(t,"Fungi;Ascomycota;Saccharomycetes;Saccharomycetales;Metschnikowiaceae;Metschnikowia;Metschnikowia_pulcherrima","GAATTGCGATACGTAATATGACTTGCAGACGTGAATCATTGAATCTTTGAACGCACATTGCGCCCCGGGGTATTCCCCAGGGCATGCGTGGGTGAGCGATATTTACTCTCAAACCTCTGGTTTGGTCCTGCTTCGGCCTAATATCAACGGCGCTAGAATAAGTTTTAGCCCCAGCCTTTTTCCTCACCCTCGTAAGACTACCCGCTGAACTTAA")

phyloseq::tax_table(frogsITS) <- t
saveRDS(frogsITS,file="html/frogsITS.rds")
taxonomy_table <- as.data.frame(tax_table(frogsITS))
clusters <- taxa_names(frogsITS)
abundances <- as.data.frame(otu_table(frogsITS))
abundance_global <- rowSums(abundances)
result_tibble <- taxonomy_table %>%
  rownames_to_column(var = "ASV") %>%  
  mutate(Abundance = abundance_global)     
result_tibble <- as_tibble(result_tibble)
result_tibble %>% datatable()
write.table(result_tibble, "html/ITS_affiliations_mod2.txt", append=TRUE, quote = FALSE, row.names = FALSE, col.names = TRUE, sep = "\t" )

This table is downloadable at the end of this document.

Compositions

cat("\n")

Downloads

The files can be used with Easy16S for an easy exploration.

You can add a column names Jean-Luc in the affiliation files to allow me a manual correction, the 7 ranks separated by a ; The abundance and multi-affiliation files can help you to choose/specify one particular affiliation. The join has to be made with the ASV sequence.

References

1. Shen W, Le S, Li Y, Hu F. SeqKit: A cross-platform and ultrafast toolkit for FASTA/q file manipulation. PloS one. 2016;11:e0163962.
2. Andrews S. FastQC a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/. 2010. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/.
3. Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016;32:3047–8.
4. Escudié F, Auer L, Bernard M, Mariadassou M, Cauquil L, Vidal K, et al. FROGS: Find, Rapidly, OTUs with Galaxy Solution. Bioinformatics. 2018;34:1287–94. doi:10.1093/bioinformatics/btx791.
5. Bernard M, Rué O, Mariadassou M, Pascal G. FROGS: a powerful tool to analyse the diversity of fungi with special management of internal transcribed spacers. Briefings in Bioinformatics. 2021;22. doi:10.1093/bib/bbab318.
6. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from illumina amplicon data. Nature methods. 2016;13:581.
7. Zhang J, Kobert K, Flouri T, Stamatakis A. PEAR: A fast and accurate illumina paired-end reAd mergeR. Bioinformatics. 2013;30:614–20.
8. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet journal. 2011;17:10–2.
9. McMurdie PJ, Holmes S. Phyloseq: An r package for reproducible interactive analysis and graphics of microbiome census data. PloS one. 2013;8:e61217.

Reuse

This document will not be accessible without prior agreement of the partners

A work by Migale Bioinformatics Facility
Université Paris-Saclay, INRAE, MaIAGE, 78350, Jouy-en-Josas, France
Université Paris-Saclay, INRAE, BioinfOmics, MIGALE bioinformatics facility, 78350, Jouy-en-Josas, France