This is an R Markdown file containing code to parse the results of a dada2 analysis into phyloseq for further analysis. It is separated into chunks that may be run independently by pressing the play button. You will need 3 files in the same location in order to run this pipeline successfully:
Recommended use: Set the individual chunks until you are content with the ouput, then knit the whole document into a PDF/html, so you have a full record of a successful run.
A custom taxonomy file may be provided instead of using the taxonomy output from dada2. This may be used to supply taxonomy derived e.g. from BLAST searches of the ASVs. Custom taxonomy files must be tab-delimited text with as many rows as the original, colum headers (for all columns except for the first column). For example:
Kingdom Phylum Class Order Family Genus Species
ESV1 Kingdomx Phylumx Classx Orderx Familyx Genusx Speciesx
ESV2 Kingdomy Phylumy Classy Ordery Familyy Genusy Speciesy
ESV3 Kingdomz Phylumz Classz Orderz Familyz Genusz Speciesz
… ESVn Kingdomy Phylumy Classy Ordery Familyy Genusy Speciesy
Friendly warning: Parsing the results of a BLAST search into this format may require some effort.
‘descriptors.txt’ should be a tab-delimited .txt table describing the samples. It must have the same length and order as the samples in seqtab_nochim.rds. To check the order and length of samples in seqtab_nochim.rds and generate a template to fill out, you may run the chunk below with “optional_sample_check” set to “TRUE”.
Any number of descriptors is possible. The sample names may be retained as one descriptor, but this is not necessary, as they will be added during parsing. For example, if there are 4 samples (order: s1, s2, s3, s4), the txt file could look as follows:
Subject Species Time
Kar1 A.thaliana 24hpi
Kar1 A.thaliana 72hpi
Mec2 S.tuberosum 24hpi
Mec3 S.tuberosum 24hpi
Finally, the file should end with an empty line, since it may throw an error otherwise. However, this is usually not a serious problem.
If you choose to use the blank file, you MUST retain the original order of the samples!
This chunk also loads required packages and defines the location of the input files. It requires the correct path as input, and allows setting the pruning of control samples and choosing generation of a phylogenetic tree. Beware: The generation of a phylogenetic tree may take several days for >1000 sequences, it is therefore recommended to only use this feature for the final analysis or small sample sets. This scricpt assumes the packages Biostrings, dada2, DECIPHER, ggplot2, ggsci, phangorn, phyloseq and stringr to be installed.
# CHANGE ME to the directory that contains 'seqtab_nochim.rds'
path = "FITS2_DADA2_results_260821"
# CHANGE ME to TRUE to list all samples and generate an empty metadata file
optional_sample_check = TRUE
# CHANGE ME to TRUE to update cuphyr
update_cuphyr = TRUE
# Initiate by loading packages and setting knit options
################# NO CHANGES NECESSARY BELOW #################
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(root.dir = paste0(path))
knitr::opts_chunk$set(message = FALSE)
knitr::opts_chunk$set(warning = FALSE)
if (update_cuphyr) {
devtools::install_github("simeross/cuphyr")
}
# Sequence and microbiome specific libraries
library(dada2)
library(Biostrings)
library(DECIPHER)
library(cuphyr)
# The export of phyloseq objects to a BIOM format and the generation of fancier
# ordination plots require the phyloseq-extended package. The first command
# installs the package that is currently on the dev brach of the author's
# repository, the second command sources some extra functions, including the
# better ordination plot implementation.
remotes::install_github("mahendra-mariadassou/phyloseq-extended", ref = "dev")
source("https://raw.githubusercontent.com/mahendra-mariadassou/phyloseq-extended/master/load-extra-functions.R" )
library(phyloseq)
#library(SIAMCAT)
# Phylogeny libraries
library(phangorn)
library(ape)
# Plotting and figure export
library(gridExtra)
library(viridis)
library(ggpubr)
# Tidyverse
library(tidyverse)
library(stringr)
# Various packages for specific analysis
library(readxl)
library(openxlsx)
library(ggpmisc)
library(betareg)
library(BBmisc)
library(aod)
library(betareg)
#install.packages('MicrobiomeStat')
library(MicrobiomeStat)
library(effectsize)
# Checks whether output path exists and creates it if not. Throws warning if
# directory exists.
outp <- paste0(path,"/analysis_output")
dir.create(file.path(outp))
if (optional_sample_check) {
seqtabcheck <- readRDS(paste0(path,"/seqtab_nochim.rds"))
samps <- rownames(seqtabcheck)
lensamps <- length(samps)
blankcol <- vector(mode = "character", length = lensamps)
blanktable <- data.frame(SampleIDs = samps, ExampleProperty1 = blankcol,
ExampleProperty2 = blankcol,
ExampleProperty3 = blankcol)
write.table(blanktable, file = paste0(path, "/descriptors_blank.txt"),
sep = "\t", row.names = F)
cat("'seqtab_nochim.rds' contains samples in the following order:\n",
samps, "\nThe number of samples in the file is:", lensamps, sep = "\n")
rm(optional_sample_check, seqtabcheck, samps,
lensamps, blankcol, blanktable, update_cuphyr)
}else{rm(optional_sample_check, update_cuphyr)}
## 'seqtab_nochim.rds' contains samples in the following order:
##
## 1-its2
## 10-its2
## 11-its2
## 12-its2
## 13-its2
## 14-its2
## 15-its2
## 16-its2
## 17-its2
## 18-its2
## 2-its2
## 3-its2
## 4-its2
## 5-its2
## 6-its2
## 7-its2
## 8-its2
## 9-its2
## NegativK-1-its2
## NegativK-2-its2
## PositivK-1-its2
## PositivK-2-its2
## PositivK-3-its2
## PositivK-4-its2
## Vann1-its2
## Vann2-its2
##
## The number of samples in the file is:
## 26
This chunk allows the adjustment of several parameters, such as setting the pruning of control samples based on keywords, requiring that a phylogenetic tree be provided or generated, defining a minimum ASV count and providing an alternative taxonomy.
# Dedicated environment containing all global analysis settings for better
# overview and collected export of settings
parameters <- new.env()
# CHANGE ME to 'TRUE' to remove control samples from the analysis or 'FALSE' to
# analyse all samples.
parameters$prune_controls = "TRUE"
# CHANGE ME to a list of unique identifiers that only occur in the names of
# samples you do NOT want to analyse. Common examples are provided.
parameters$controls = c("Pos", "H2O", "Neg", "Kontr", "Contr", "POSK")
# CHANGE ME to 'TRUE' to remove certain taxonomic groups from the analysis by
# name. This is useful to exclude non-target organisms or noise from organelles
# such as Chloroplasts and Mitochondria. It is recommended to first look at all
# data before using this setting.
parameters$prune_noise_taxgroups = "FALSE"
# CHANGE ME to define the taxonomic groups to be removed as noise.
parameters$noise_taxgroups = c("Chloroplast", "Mitochondria")
# CHANGE ME to a number of ASV counts [~reads] that analyzed samples should
# minimally have. Samples with lower ASV counts than 'minread' will be pruned.
# Set to 0 to not prune any samples.
parameters$minASVcount = 3000
# CHANGE ME to 'TRUE', if you want to provide a custom taxonomy table instead
# of using the default dada2 output ('taxa.rds').
parameters$customTax = "TRUE"
# CHANGE ME to the location of the custom taxonomy file. This only matters if
# parameters$customTax='TRUE', otherwise it will be ignored.
parameters$taxfile = "FITS2_DADA2_results_260821/custom_BLAST_taxonomy_nt.txt"
# CHANGE ME to 'TRUE' to generate a phylogenetic tree. This process takes a
# long time depending on the number of sequences (up to days for thousands).
# If a tree is provided as 'phylotree.rds' in 'path', then it will be used
# regardless of the value of 'parameters$maketree'
parameters$maketree = "FALSE"
# CHANGE ME to 'TRUE' to root the used phylogenetic tree (if one exists) on the
# leaf with the longest branch (outgroup). This makes analyses that rely on the
# phylogenetic tree reproducible instead of picking a random leaf as root when
# calculating UNIFRAC distances. Implementation based on
# http://john-quensen.com/r/unifrac-and-tree-roots/ and answers in
# https://github.com/joey711/phyloseq/issues/597
parameters$roottree = "TRUE"
## CHANGE ME to 'TRUE' to export all generated phyloseq objects as .biom
## objects
parameters$biom_export = "FALSE"
This chunk loads the input data into a usable format.This chunk does not require any user inputs. If no phylogenetic tree with the name ‘phylotree.rds’ was provided and ‘parameters$maketree=“TRUE”’, it will be calculated here. The phylogenetic tree is necessary for certain plots that incorporate ‘true’ taxonomic relationships beyond the annotations, such as PCoA.
############### NO NEED FOR CHANGES BELOW ############### Make dedicated
############### environments to contain temporary values and manage other
############### objects
tmp <- new.env()
plots <- new.env()
set <- new.env()
# Read in variables
tmp$seqtabp <- readRDS(paste0(path, "/seqtab_nochim.rds"))
if (parameters$customTax == "TRUE") {
tmp$taxap <- read.delim(parameters$taxfile, header = TRUE, sep = "\t")
rownames(tmp$taxap) <- colnames(tmp$seqtabp)
tmp$taxap <- as.matrix(tmp$taxap)
} else {
tmp$taxap <- readRDS(paste0(path, "/taxa.rds"))
}
tmp$samp_table <- read.delim(paste0(path, "/descriptors.txt"), header = TRUE, sep = "\t")
tmp$samp_list <- rownames(tmp$seqtabp)
# Check if descriptors has the same samples as seqtabp
if (length(tmp$samp_table[, 1]) != length(tmp$samp_list)) {
stop("There are ", length(tmp$samp_table[, 1]), " samples in 'descriptors.txt', but ",
length(tmp$samp_list), " samples in 'seqtab_nochim.rds'. Please make sure that the correct samples
are contained in descriptors.txt.
You may use 'optional_sample_check <- TRUE' in the first chunk to generate an
empty template for 'descriptors.txt'")
} else if (!identical(tmp$samp_table[, 1], tmp$samp_list)) {
warning("Warning: The samples in 'descriptors.txt' do not have the same names
or order as the samples in 'seqtab_nochim.rds'. This may be fine if
abbreviated names were used or the sample names are not contained in
the first column of 'descriptors.txt'. Double-checking never hurts!")
}
# generate phylogenetic tree of ASVs only if there is no file called
# 'phylotree.rds' in the working directory and 'parameters$maketree' is 'TRUE'
if (!file.exists(paste0(path, "/phylotree.rds"))) {
if (parameters$maketree == "TRUE") {
tmp$ASVs <- getSequences(tmp$seqtabp)
names(tmp$ASVs) <- tmp$ASVs
tmp$ASV_align <- AlignSeqs(DNAStringSet(tmp$ASVs), anchor = NA)
tmp$ASV_phang <- phyDat(as(tmp$ASV_align, "matrix"), type = "DNA")
tmp$dm <- dist.ml(tmp$ASV_phang)
tmp$treeNJ <- NJ(tmp$dm)
tmp$fit <- pml(tmp$treeNJ, data = tmp$ASV_phang)
tmp$fitGTR <- update(tmp$fit, k = 4, inv = 0.2)
tmp$fitGTR <- optim.pml(tmp$fitGTR, model = "GTR", optInv = TRUE, optGamma = TRUE,
rearrangement = "stochastic", control = pml.control(trace = 0))
saveRDS(tmp$fitGTR, file = paste0(path, "/phylotree.rds"))
}
}
## parse into phyloseq object
row.names(tmp$samp_table) <- tmp$samp_list
if (file.exists(paste0(path, "/phylotree.rds"))) {
tmp$treep <- readRDS(paste0(path, "/phylotree.rds"))
p <- phyloseq(otu_table(tmp$seqtabp, taxa_are_rows = FALSE), sample_data(tmp$samp_table),
tax_table(tmp$taxap), phy_tree(tmp$treep$tree))
} else {
p <- phyloseq(otu_table(tmp$seqtabp, taxa_are_rows = FALSE), sample_data(tmp$samp_table),
tax_table(tmp$taxap))
}
## Adding nucleotide info and giving sequences ASV## identifiers
tmp$ASV_sequences <- Biostrings::DNAStringSet(taxa_names(p))
taxa_names(p) <- paste0("ASV", seq(ntaxa(p)))
names(tmp$ASV_sequences) <- taxa_names(p)
p <- merge_phyloseq(p, tmp$ASV_sequences)
## optional pruning
if (parameters$prune_controls == "TRUE") {
if (!is.null(parameters$controls)) {
tmp$samp_clean <- tmp$samp_list[!tmp$samp_list %in% grep(paste0(parameters$controls,
collapse = "|"), tmp$samp_list, value = T)]
tmp$contr_pruned <- setdiff(tmp$samp_list, tmp$samp_clean)
ps <- prune_samples(tmp$samp_clean, p)
# Physeq object for Just controls
ps.contr <- prune_samples(tmp$contr_pruned, p)
ps.contr <- prune_taxa(taxa_sums(ps.contr) > 0, ps.contr)
ps.transcontr <- transform_sample_counts(ps.contr, function(ASV) ASV/sum(ASV))
message(cat("\n", "Number of control samples that were pruned and will not be analysed:\n",
length(tmp$samp_list) - length(tmp$samp_clean), "\n", "The following controls were pruned:\n",
tmp$contr_pruned, "The controls are contained in a separate phyloseq object: ps.contr",
"\n", sep = "\n"))
} else {
warning(cat("\n\nparameters$prune_controls is TRUE but 'parameters$controls' is empty.
No samples were pruned.\n\n"))
}
} else {
ps <- p
}
##
##
## Number of control samples that were pruned and will not be analysed:
##
## 6
##
##
## The following controls were pruned:
##
## NegativK-1-its2
## NegativK-2-its2
## PositivK-1-its2
## PositivK-2-its2
## PositivK-3-its2
## PositivK-4-its2
## The controls are contained in a separate phyloseq object: ps.contr
# Prune ASVs defined as noise
if (parameters$prune_noise_taxgroups == "TRUE") {
tmp$ps_taxlvls <- colnames(tax_table(ps))
tmp$noise_ASVs <- character(0)
for (lvl in tmp$ps_taxlvls) {
tmp$noise_ASVs <- c(tmp$noise_ASVs, cuphyr::list_subset_ASVs(physeq = ps,
subv = parameters$noise_taxgroups, taxlvlsub = lvl))
}
tmp$noise_ASVs <- unique(tmp$noise_ASVs)
tmp$no_noise_ASVs <- colnames(otu_table(ps))
tmp$no_noise_ASVs <- setdiff(tmp$no_noise_ASVs, tmp$noise_ASVs)
if (length(tmp$noise_ASVs) > 0) {
ps <- prune_taxa(tmp$no_noise_ASVs, ps)
tmp$no_noise_ps <- ps
cat(length(tmp$noise_ASVs), "ASVs were pruned because they belonged to the following
taxonomic groups:\n")
cat(parameters$noise_taxgroups, "\n", sep = "\n")
} else {
cat("No ASVs were recognized as belonging to the following taxonomic groups
defined as noise:\n")
cat(parameters$noise_taxgroups, "\n", sep = "\n")
}
}
# Prune samples with fewer than reads than minASVcount
if (parameters$minASVcount > 0) {
tmp$samp_pruned <- names(which(sample_sums(ps) < parameters$minASVcount))
ps <- prune_samples(sample_sums(ps) >= parameters$minASVcount, ps)
if (length(tmp$samp_pruned) > 0) {
cat("The following samples were pruned because ASV counts were lower than",
parameters$minASVcount, ":\n")
cat(tmp$samp_pruned, "\n", sep = "\n")
}
}
## The following samples were pruned because ASV counts were lower than 3000 :
## Vann1-its2
## Vann2-its2
# Remove 0 count ASVs (e.g. control ASVs that remain) from the base object
ps <- prune_taxa(taxa_sums(ps) > 0, ps)
# Get a tbl of the base object for easier access in some phyloseq-independent
# analyses. Takes some seconds, potentially up to minutes.
ps_tbl <- as_tibble(psmelt(ps))
# Transformed per sample (per-sample relative abundance)
ps.trans <- transform_sample_counts(ps, function(ASV) ASV/sum(ASV))
# Read NDVI values as numeric
sample_data(ps)[["ndvi"]] <- as.numeric(sample_data(ps)[["ndvi"]])
sample_data(ps.trans)[["ndvi"]] <- as.numeric(sample_data(ps.trans)[["ndvi"]])
# Get a tbl of the base object for easier access in some phyloseq-independent
# analyses. Takes some seconds, potentially up to minutes.
ps_tbl <- as_tibble(psmelt(ps))
ps_trans_tbl <- as_tibble(psmelt(ps.trans))
# Condensing to Abundance per Genus and Sample
genus_abundance_tbl_per_sample <- ps_trans_tbl %>%
group_by(Genus, Sample) %>%
mutate(Genus_Sample_Abundance = sum(Abundance)) %>%
select(Genus, Sample, ndvi, Genus_Sample_Abundance, Alias) %>%
unique()
if (parameters$roottree == "TRUE" && parameters$maketree == "TRUE") {
phyloseq::phy_tree(ps) <- cuphyr::root_tree_in_outgroup(physeq = ps)
}
if (parameters$biom_export == "TRUE") {
suppressWarnings(phyloseq.extended::write_phyloseq(p, biom_file = paste0(path,
"all_samples.biom"), biom_format = "standard"))
suppressWarnings(phyloseq.extended::write_phyloseq(ps, biom_file = file.path(path,
"samples_without_controls.biom"), biom_format = "standard"))
suppressWarnings(phyloseq.extended::write_phyloseq(ps.trans, biom_file = file.path(path,
"samples_without_controls_rel_abundance.biom"), biom_format = "standard"))
suppressWarnings(phyloseq.extended::write_phyloseq(ps.contr, biom_file = file.path(path,
"just_controls.biom"), biom_format = "standard"))
}
ps
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 1671 taxa and 18 samples ]
## sample_data() Sample Data: [ 18 samples by 19 sample variables ]
## tax_table() Taxonomy Table: [ 1671 taxa by 7 taxonomic ranks ]
## refseq() DNAStringSet: [ 1671 reference sequences ]
The chunks below will produce various plots and other output. Each chunk is headed by a description of the output and may contain some parameters to adjust the output.
This chunk sets the background structure and color palette. Viridis was chosen because it is optimized for grey-scale printing and various types of color blindness and More info on the Viridis palette can be found on the Viridis info page. It also establishes save_plot as a shorter variant of ggsave with customized date-time structure to save plots with the same name mulitple times instead of overwriting them (overwriting can be triggered with overwrite=TRUE).
##### Optional settings (sensible defaults) #####
# Can be changed to adjust the output format for all plots. Default "pdf",
# possible "eps"/"ps", "tex" (pictex), "jpeg", "tiff", "png", "bmp" and "svg"
parameters$output_format = "pdf"
# Can be changed to preferred ggplot2 theme. Recommended: "theme_bw()".
theme_set(theme_bw())
############### NO NEED FOR CHANGES BELOW ###############
my_scale_col <- scale_color_viridis(discrete = TRUE)
my_scale_fill <- scale_fill_viridis(discrete = TRUE)
# Custom, more narrow color ranges based on viridis
# Base order to have adjacent colors be distinct from each other
tmp$sort_colors <- c(rbind(c(1:5), c(6:10), c(11:15), c(16:20)))
# Customized vectors
tmp$n_col <- 20
tmp$viridis_greens <- viridis(tmp$n_col, option = "D", begin = 0.85,
end = 0.7)[tmp$sort_colors]
tmp$viridis_reds <- viridis(tmp$n_col, option = "B", begin = 0.7,
end = 0.5)[tmp$sort_colors]
tmp$viridis_blues <- viridis(tmp$n_col, option = "D", begin = 0.2,
end = 0.4)[tmp$sort_colors]
tmp$viridis_yellows <- viridis(tmp$n_col, option = "D", begin = 1,
end = 0.9)[tmp$sort_colors]
tmp$viridis_dark <- viridis(tmp$n_col, option = "A", begin = 0,
end = 0.1)[tmp$sort_colors]
tmp$viridis_light <- viridis(tmp$n_col, option = "A", begin = 1,
end = 0.9)[tmp$sort_colors]
# Collected list that is available in the global environment
sub_viridis <- list(tmp$viridis_greens, tmp$viridis_blues, tmp$viridis_yellows,
tmp$viridis_light, tmp$viridis_reds, tmp$viridis_dark)
names(sub_viridis) <- c("greens", "blues", "yellows", "lights", "reds", "darks")
tmp$out <- paste0(".", parameters$output_format)
#################### Function ############################
# Generic save function for plots that checks whether file exists and if so,
# creates a new one with d/m/y+time info to avoid overwriting. Overwriting can
# be triggered with overwrite = TRUE. Width, height and resolution are taken
# from parameters in the 'set' environment or set to 20x20 cm with 300dpi.
save_plot <- function(
pl, filetype = ".pdf", plot_name = "my_plot", overwrite=FALSE){
wp <- if (!is.null(set$wp)) set$wp else 20
hp <- if (!is.null(set$hp)) set$hp else 20
res <- if (!is.null(set$res)) set$res else 300
name <- paste0("/", plot_name,filetype)
if (file.exists(paste0(outp, name)) & !overwrite) {
name <- paste0("/", plot_name, "_",
format(Sys.time(), "%d-%m-%y_%H%M%S"),filetype)}
ggsave(file.path(outp, name), pl,
width = wp, height = hp, unit = "cm", dpi = res)
}
################################################
This chunk plots the absolute abundance of all samples (including controls) and all samples without controls and other trimmed samples.
# CHANGE ME to the sample group for color coding. Accepted values are the column
# headers in the descriptor file.
set$color_by = "mel_mol_asv"
##### Optional settings (sensible defaults) #####
# Can be changed to change the width (in cm) of the saved plot.
set$wp = 17
# Can be changed to change the height (in cm) of the saved plot.
set$hp = 20
# Can be changed to change the resolution (in dpi) of the saved plot.
set$res = 300
############### NO NEED FOR CHANGES BELOW ###############
# Rank samples
set$ranked <- cuphyr::make_ranked_sums(p, myset = tmp$subset_id)
set$ranked_ps <- cuphyr::make_ranked_sums(ps, myset = tmp$subset_id)
set$ymax <- max(set$ranked$Abundance)
set$ymax <- set$ymax + round(set$ymax/10)
set$xmax <- nrow(set$ranked) + 1
set$title2 <- "Samples (without controls)"
# Stabilize colors
set$color_vars <- set$ranked[,set$color_by] %>%
unlist() %>% as.character() %>% unique()
set$color_vars <- sort(set$color_vars)
set$color_varsPalette <- viridis(length(set$color_vars))
names(set$color_varsPalette) <- set$color_vars
set$my_scale_fill <- scale_fill_manual(values = set$color_varsPalette)
# plot
plots$overview_all <- ggplot(data = set$ranked, aes(x = Rank, y = Abundance)) +
aes_string(fill = set$color_by) +
geom_col() + set$my_scale_fill + ggtitle("All samples") + ylim(0, set$ymax) +
xlim(0,set$xmax) + ylab("ASV counts ('reads')")
if (length(tmp$noise_ASVs) > 0) {
set$ranked_nonoise <- cuphyr::make_ranked_sums(
tmp$no_noise_ps, myset = tmp$subset_id)
plots$overview_noise <- ggplot(
data = set$ranked_nonoise, aes(x = Rank, y = Abundance)) +
aes_string(fill = set$color_by) +
geom_col() + set$my_scale_fill +
ggtitle("Samples (without controls), noise ASVs removed") +
ylim(0, set$ymax) +
xlim(0,set$xmax) + ylab("ASV counts ('reads')")
}
if (parameters$minASVcount > 0) {
plots$overview_all <- plots$overview_all +
geom_hline(yintercept = parameters$minASVcount, linetype = "dashed") +
ggtitle("All samples (ASV count cutoff indicated)")
set$title2 <- "Samples (without controls and low count samps)"
}
plots$overview_ps <- ggplot(data = set$ranked_ps, aes(x = Rank, y = Abundance)) +
aes_string(fill = set$color_by) +
geom_col() + set$my_scale_fill + ggtitle(set$title2) + ylim(0, set$ymax) +
xlim(0,set$xmax) + ylab("ASV counts ('reads')")
plots$combo_overview <- ggarrange(
plots$overview_all, plots$overview_ps, nrow = 2, align = "v",
common.legend = TRUE, legend = "right")
if (parameters$minASVcount > 0) {
plots$combo_overview <- ggarrange(
plots$overview_all, plots$overview_noise, plots$overview_ps,
nrow = 3, align = "v",
common.legend = TRUE, legend = "right")
}
#Save plots
save_plot(plots$combo_overview, plot_name = "Overview_all_and_pruned",
filetype = tmp$out)
#Clean up plot parameters
rm(list = ls(set), envir = set)
#Print plots
plots$combo_overview
This chunk generates an overview over the controls (positive AND negative)
# CHANGE ME to the desired sample categories on the x-axis. In this case it
# should be the Sample names.
set$x_axis_value = "SampleIDs"
# CHANGE ME to the taxonomic level for color coding. Use "OTU" for ASVs,
# "Genus", "Species" or "OTU" recommended to compare pos. controls.
set$color_by_taxlvl = "Species"
# CHANGE ME to the taxonomic level for labeling the tree tips (if phylogenetic
# tree is available). Use "OTU" for ASVs.
set$label_by_taxlvl = "OTU"
# CHANGE ME to a sample category to shape the tree tip labels by (if
# phylogenetic tree is available).
set$label_shape_by = "Symptom"
##### Optional settings (sensible defaults) #####
# Can be changed to generate a tree for just the control sequences IF no
# phylogenetic tree for all seuquences is provided. This may slow down this
# chunk when running it for the first time
set$control_tree = TRUE
# Can be changed to change the width (in cm) of the saved plot.
set$wp = 17
# Can be changed to change the height (in cm) of the saved plot.
set$hp = 20
# Can be changed to change the resolution (in dpi) of the saved plot.
set$res = 300
############### NO NEED FOR CHANGES BELOW ###############
if (set$control_tree & class(try(phy_tree(ps.transcontr),
silent = TRUE)) == "try-error") {
# generate phylogenetic tree of ASVs only if there is no file called
# 'phylotree.rds' in the working directory and 'parameters$maketree' is "TRUE"
if (!file.exists(paste0(path, "/controls_phylotree.rds"))) {
set$ASVs <- phyloseq::refseq(ps.transcontr)
set$ASV_align <- AlignSeqs(set$ASVs, anchor = NA)
set$ASV_phang <- phyDat(as(set$ASV_align, "matrix"), type = "DNA")
set$dm <- dist.ml(set$ASV_phang)
set$treeNJ <- NJ(set$dm)
set$fit <- pml(set$treeNJ, data = set$ASV_phang)
set$fitGTR <- update(set$fit, k = 4, inv = 0.2)
set$fitGTR <- optim.pml(set$fitGTR, model = "GTR",
optInv = TRUE, optGamma = TRUE,
rearrangement = "stochastic",
control = pml.control(trace = 0))
saveRDS(set$fitGTR, file = paste0(path, "/controls_phylotree.rds"))}
set$fitGTR <- readRDS(paste0(path, "/controls_phylotree.rds"))
phyloseq::phy_tree(ps.transcontr) <- set$fitGTR$tree
}
plots$topnpplot <- plot_bar(ps.contr, x = set$x_axis_value,
fill = set$color_by_taxlvl) + my_scale_fill +
theme(axis.title.x = element_blank(), legend.position = "none",
legend.key.size = unit(3, "mm")) +
ylab("ASV counts") + guides(col = guide_legend(ncol = 3))
plots$topntplot <- plot_bar(ps.transcontr, x = set$x_axis_value,
fill = set$color_by_taxlvl) + my_scale_fill +
theme(axis.title.x = element_blank(), legend.position = "none",
legend.key.size = unit(3, "mm")) +
ylab("Relative abundance") + guides(col = guide_legend(ncol = 3))
plots$combo_contr <- ggarrange(plots$topnpplot, plots$topntplot, ncol = 2,
labels = c("A", "B"), align = "hv",
common.legend = TRUE, legend = "right")
if (class(try(phy_tree(ps.transcontr), silent = TRUE)) != "try-error") {
plots$tre <- plot_tree(
ps.transcontr, ladderize = "left", label.tips = set$label_by_taxlvl,
color = "abundance", text.size = 2.5, shape = set$label_shape_by) +
scale_color_viridis_c(aesthetics = c("color","fill")) +
theme(legend.position = "left", panel.border = element_blank())
plots$combo_contr <- ggarrange(plots$tre, ggarrange(plots$topnpplot,
plots$topntplot, ncol = 2,
labels = c("B", "C"), align = "hv",
common.legend = TRUE, legend = "right"),
nrow = 2, legend = "right", labels = c("A"))
}
# save
save_plot(plots$combo_contr, plot_name = "Controls", filetype = tmp$out)
plots$combo_contr
This chunk lists the top n most abundant taxonomic terms at a given
level. Change the function parameters to the desired values. For more
info, check help page of the function with
?cuphyr::abundant_tax_physeq()
. Change ‘ignore_na’ to
include/exclude NA values at the given level.
#The character vector can later be accessed by calling 'tmp$tops'
tmp$tops <- cuphyr::abundant_tax_physeq(physeq = ps,
lvl = "Genus",
top = 100,
output_format = "tops",
ignore_na = TRUE,
silent = FALSE)
##
## The top 100 most abundant annotated groups at the taxonomic level 'Genus' are:
## Mrakia
## Candida
## Mortierella
## Juxtiphoma
## Sistotrema
## Cladosporium
## Gibellulopsis
## Alternaria
## Chloridium
## Fusarium
## Solicoccozyma
## Sporobolomyces
## Umbelopsis
## Trichosporiella
## Tetracladium
## Aspergillus
## Cadophora
## Vishniacozyma
## Colletotrichum
## Botrytis
## Paraphaeosphaeria
## 'uncultured fungus'
## Urceolella
## Tausonia
## Laetinaevia
## Podospora
## Minimedusa
## Exophiala
## Rhodotorula
## Acremonium
## Alpinaria
## Naganishia
## Cystofilobasidium
## Plectosphaerella
## Papiliotrema
## Dioszegia
## Sporidesmium
## Holtermanniella
## Trichocladium
## Talaromyces
## Chrysosporium
## Barnettozyma
## Ophiosphaerella
## Sphaerobolus
## Coniochaeta
## Apiotrichum
## Paraphoma
## Trematosphaeria
## Delitschia
## Chordomyces
## 'uncultured Orbiliales'
## Protoventuria
## Neoascochyta
## Leucosporidium
## Leptosphaeria
## Pleotrichocladium
## Devriesia
## Glonium
## Verticillium
## Pseudeurotium
## Halenospora
## 'uncultured Spizellomycetales'
## Truncatella
## Cephalosporium
## Hyaloscypha
## Cladophialophora
## Coprinus
## Cyberlindnera
## Didymella
## Dendryphion
## Arthopyrenia
## Gorgomyces
## Waitea
## 'uncultured Ichthyophonida'
## 'uncultured Agaricales'
## 'uncultured Hypocreales'
## Sakaguchia
## Apodus
## Pseudoanguillospora
## Rhizoctonia
## Rhizophagus
## Trichoderma
## Nullicamyces
## Stemphylium
## 'uncultured Glomerales'
## 'uncultured Basidiomycota'
## Spizellomyces
## Neopyrenochaeta
## Zasmidium
## Penicillium
## 'uncultured Ascomycota'
## Ochroconis
## Fimicolochytrium
## Pseudogymnoascus
## Lachnellula
## Polymyxa
## Sordaria
## Phoma
## Neohendersonia
## Neohelicomyces
This chunk gives an overview of the number of ASVs belonging to which Phylum
fits1_list <- cuphyr::list_subset_ASVs(subv = c("Fungi"), taxlvlsub = "Kingdom")
cuphyr::summarise_physeq(physeq = ps,
ASV_sublist = fits1_list,
sublist_id = "Fungi", samp_names = FALSE)
## There are 1671 ASVs in the phyloseq object 'ps'.
## Of this, 1502 belong to the provided subset (Fungi), representing 98.81 percent of abundance per sample on average.
# Total ASV counts
ps_tbl %>% select(OTU, Abundance) %>% summarise(total_sum = sum(Abundance))
## # A tibble: 1 × 1
## total_sum
## <int>
## 1 888567
# Total ASV counts per phylum
ps_tbl %>% select(OTU, Kingdom, Abundance) %>% group_by(Kingdom) %>% summarise(Abundance_sum = sum(Abundance))
## # A tibble: 4 × 2
## Kingdom Abundance_sum
## <chr> <int>
## 1 Fungi 878383
## 2 Metazoa 4195
## 3 Viridiplantae 2265
## 4 <NA> 3724
# Percentage of ASV counts belonging to Fungi
its2_percentage = 878383/888567 # ASV counts Fungi / Total ASV counts
its2_percentage
## [1] 0.9885388
This chunk plots abundance of the Top n ASVs or taxa at a given level as a bar plot, giving an insight into the presence of the n ASV and most common taxa for the primary and secondary parameters. The default for n is set at 20, a larger n may lead to delay/skipping of the plot in standard out, but it should be saved as a PDF regardless for ASVs. For taxa, a large n may lead to unreadable plots. The chunk does not require any input, but it is possible to adjust the default ‘n’, and to change width, height and resolution of the PDF-output if necessary.
# CHANGE ME to the desired sample categories on the x-axis.
# Accepted values are the column headers in the descriptor file.
set$x_axis_value = "ndvi"
# CHANGE ME to the taxonomic level of interest (color coding). Accepted values
# are the column headers in your descriptor file.
set$taxlvl = "Genus"
# CHANGE ME to change the number of Top n taxa to be plotted at
# taxlvl.
set$top_n = 10
# Can be changed to include (FALSE) or exclude (TRUE) NA values in the barplot
set$ignore_na = FALSE
# CHANGE ME to an entry at the chosen taxonomic level you want to highlight.
# Comment out to not highlight anything.
#set$highlight = "Meloidogyne"
##### Optional settings (sensible defaults) #####
# Can be changed to change the width (in cm) of the saved plot.
set$wp = 20
# Can be changed to change the height (in cm) of the saved plot.
set$hp = 13
# Can be changed to change the resolution (in dpi) of the saved plot.
set$res = 300
# Can be changed to change the y-axis label
set$y_axis_label = "Relative abundance"
# Can be changed to change the x-axis label
set$x_axis_label = "Sample"
############### NO NEED FOR CHANGES BELOW ###############
# Estimate Alpha-diversity (Shannon)
set$alpha_div_ps_trans <- estimate_richness(ps.trans, measures = "Shannon") %>%
as_tibble(rownames = "Sample") #%>%
# rename("Shannon" = Simpson)
# Make physeq objects of top n taxa and top n ASVs
set$ps.topnTax <- cuphyr::abundant_tax_physeq(ps.trans, lvl = set$taxlvl,
top = set$top_n,
ignore_na = set$ignore_na)
# Plot
set$my_scale_fill <- my_scale_fill
set$topntax_tbl <- psmelt(set$ps.topnTax) %>%
as_tibble() %>%
left_join(set$alpha_div_ps_trans, by = "Sample") %>%
select(Genus, Alias, ndvi, Abundance, Shannon) %>%
filter(Abundance > 0) %>%
group_by(Genus, Alias, ndvi, Shannon) %>%
summarise(Abundance = sum(Abundance)) %>%
arrange(ndvi) %>%
mutate(ndvi_rank = c(1:length(ndvi)))
plots$topn_tax_custom <- ggplot(set$topntax_tbl, aes(x = fct_reorder(Alias, ndvi),
y = Abundance,
fill = Genus)) +
#title = paste0("Top ", set$top_n, " ", set$taxlvl))) +
geom_col(color = "black") +
set$my_scale_fill +
ylab(set$y_axis_label) +
xlab(set$x_axis_label) +
theme(strip.background = element_blank(),
legend.position = "bottom")
plots$ndvi_dot_plot <- ggplot(set$topntax_tbl, aes(fct_reorder(Alias, ndvi),
y = ndvi)) +
geom_point() +
theme(strip.background = element_blank(),
axis.title.x=element_blank()) +
ylab("NDVI")
plots$shannon_dot_plot <- ggplot(set$topntax_tbl,
aes(fct_reorder(Alias, ndvi),
y = Shannon)) +
geom_point() +
theme(strip.background = element_blank(),
axis.title.x=element_blank()) +
ylab("Shannon")
plots$combo_topn_custom <- ggarrange(plots$ndvi_dot_plot,
plots$shannon_dot_plot,
plots$topn_tax_custom,
nrow = 3,
heights = c(1, 1, 3),
align = "v")
save_plot(plots$combo_topn_custom, plot_name = paste0("Customized_NDVI_Shannon_plot"),
filetype = tmp$out)
plots$combo_topn_custom
set$my_formula <- y ~ x
set$plot_title <- "Fungi (FITS2)"
topntax_data <- set$topntax_tbl %>%
mutate(Taxa = 'fits2') %>%
ungroup() %>%
select(Alias, ndvi, Shannon, Taxa) %>%
distinct()
write.csv(topntax_data, file = "../topntax_all_taxa/topntax_data_fits2.csv")
# Create properly formatted tibble with columns Sample, ndvi_01 (ndvi translated to (0, 1) interval) and one column for each genus
# containing the sample abundances for that genus.
ldf <- data.frame(genus_abundance_tbl_per_sample %>% pivot_wider(id_cols = c('Sample', 'ndvi'), names_from = 'Genus', values_from = 'Genus_Sample_Abundance'))
ldf_genus_data <- data.frame(ldf) %>% select(!c('Sample', 'ndvi'))
colnames(ldf_genus_data) <- gsub(' ', '.', colnames(ldf_genus_data))
ldf <- cbind.data.frame(
Sample = ldf$Sample,
ndvi_01 = (ldf$ndvi + 1) / 2.0
)
ldf <- tibble(cbind(ldf, ldf_genus_data))
n_samples_by_genus <- data.frame(ldf_genus_data > 0) %>% mutate_if(is.logical, as.numeric) %>% colSums() %>% sort(decreasing = TRUE)
keep_n <- 100 # Maximum number of genuses to include in the analysis
top_n_occurence_genuses <- names(n_samples_by_genus[1:keep_n])
top_n_occurence_genuses <- top_n_occurence_genuses[!is.na(top_n_occurence_genuses)]
l_genus_ldf <- ldf %>% select(all_of(top_n_occurence_genuses))
l_genus_ldf_transposed <- data.frame(t(l_genus_ldf))
l_meta_ldf <- ldf %>% select('ndvi_01')
l_model <- linda(
l_genus_ldf_transposed,
l_meta_ldf,
formula = '~ ndvi_01',
feature.dat.type = 'proportion',
is.winsor = FALSE,
alpha = 0.05
)
## 0 features are filtered!
## The filtered data has 18 samples and 100 features will be tested!
## Fit linear models ...
## Completed.
# Print model info
l_model
## $variables
## [1] "ndvi_01"
##
## $bias
## [1] -0.06003912
##
## $output
## $output$ndvi_01
## baseMean log2FoldChange lfcSE
## Candida 64855.7339 0.223427960 0.29625914
## Mrakia 137712.5246 -0.126149897 0.13824709
## Colletotrichum 9975.0863 -0.555137076 0.34043978
## Cladosporium 40663.1338 0.958216259 0.24164878
## Sporobolomyces 15851.7473 1.615421093 0.31411693
## Juxtiphoma 60592.5372 -0.003133777 0.13831708
## Sistotrema 49356.2769 0.024813154 0.25181444
## Gibellulopsis 31844.0120 0.024176825 0.15775986
## Botrytis 17417.2529 0.664397243 0.30134099
## Podospora 9177.1238 -0.291139885 0.23814170
## Alternaria 30206.5050 -0.119394651 0.18607697
## Fusarium 25205.8716 -0.366581496 0.21721201
## Mortierella 97189.2687 0.074171290 0.10057144
## Cadophora 21893.8184 -0.324458149 0.09727133
## Aspergillus 23934.0302 0.212046916 0.06210173
## Laetinaevia 11010.7263 -0.229434231 0.22306853
## Paraphaeosphaeria 17523.4236 -0.119369481 0.14381724
## Tetracladium 19683.1695 -0.473325140 0.20726442
## Solicoccozyma 28483.9636 0.011181980 0.10380672
## Chloridium 29641.4667 -0.315352933 0.12511179
## Trichosporiella 19578.7390 -0.722571471 0.18211055
## Vishniacozyma 16229.8737 0.883288344 0.28199229
## Umbelopsis 24225.0522 0.274862969 0.17646619
## Plectosphaerella 4286.3430 0.642633262 0.28259447
## Tausonia 12318.6719 -0.105809988 0.19900516
## Chordomyces 2045.6662 1.037165724 0.28996476
## Minimedusa 10394.5710 0.367241472 0.17080732
## Urceolella 14279.9809 -0.283974754 0.10316279
## Naganishia 6543.3855 0.400619651 0.17028459
## Acremonium 7127.7850 0.306642537 0.19276356
## X.uncultured.fungus. 15910.3745 0.131545738 0.10951640
## Talaromyces 3907.3448 0.207260292 0.32210852
## Holtermanniella 4875.6600 0.189052140 0.18132252
## Sporidesmium 5287.4513 -0.173566541 0.14323542
## Protoventuria 2869.6767 -0.042575329 0.16328045
## Trichocladium 5011.6517 -0.163317004 0.12665952
## Gorgomyces 992.4232 -0.982940191 0.29618703
## Papiliotrema 5207.4970 0.033355458 0.16379285
## Ophiosphaerella 3430.3770 -0.069319372 0.11596455
## Pseudeurotium 2052.5011 0.348650782 0.31921908
## Coniochaeta 3102.3335 -0.327716837 0.14880418
## Exophiala 7794.7155 -0.189252171 0.14667745
## NA. 7299.8862 0.170515771 0.12505966
## Sakaguchia 1172.6853 -0.329665815 0.21313105
## Pseudoanguillospora 970.3718 -0.056484147 0.30338656
## Halenospora 2187.0233 -0.341543400 0.16392615
## Pleotrichocladium 2059.7164 -0.423911605 0.28149263
## Cephalosporium 2114.8551 -0.158147249 0.17447955
## X.uncultured.Spizellomycetales. 1851.2812 -0.119947362 0.32879296
## Verticillium 2382.0107 0.391487585 0.19095141
## Pseudogymnoascus 1044.1890 0.139213124 0.19405191
## Devriesia 2646.5150 0.072390136 0.12140692
## Polymyxa 914.2938 -0.489528074 0.17254518
## Apodus 1188.6065 0.422169395 0.25272443
## Arthopyrenia 1706.0135 0.065833583 0.14541611
## Zasmidium 1124.8244 0.350946743 0.15187707
## X.uncultured.Agaricales. 1006.1689 0.151604556 0.40180240
## X.uncultured.Glomerales. 1124.9771 0.078365323 0.20223420
## Ochroconis 1024.0389 -0.097038195 0.18421722
## X.uncultured.Basidiomycota. 1063.0512 -0.086452242 0.23249945
## Microdochium 553.3013 0.042877532 0.29280961
## X.uncultured.Hypocreales. 1438.7679 -0.123848877 0.20716917
## X.uncultured.Mortierellales. 604.1388 0.342821980 0.31073789
## X.uncultured.Ascomycota. 1038.8782 0.213464170 0.25042139
## Allovahlkampfia 584.6582 -0.092153191 0.25210743
## Rhodotorula 4085.0962 1.029864285 0.41127426
## Dioszegia 2071.6538 1.061786375 0.49955429
## Alpinaria 1953.8021 0.170573036 0.60055393
## Leucosporidium 1400.4022 0.824491727 0.36171309
## Trematosphaeria 1522.2950 -0.933633545 0.30043503
## Paraphoma 2093.4314 -0.538998661 0.49466838
## Neoascochyta 1708.7532 0.072967586 0.41829934
## Barnettozyma 2458.8383 0.544038170 0.42964477
## Apiotrichum 1900.7476 0.050058510 0.44301095
## Waitea 1090.9631 0.279643651 0.40086194
## Dendryphion 1400.4955 -0.556690470 0.25411140
## Hyaloscypha 1545.4426 -0.526521960 0.28568895
## Neopyrenochaeta 976.3556 -0.544164691 0.26491958
## Cladophialophora 1811.1913 -0.401131745 0.18253724
## Nullicamyces 1138.5811 0.411352123 0.21819542
## Rhizophagus 738.4522 0.775040286 0.41413520
## Spizellomyces 1006.4791 -0.248987420 0.25291903
## Neohendersonia 946.5213 0.225157790 0.18357875
## Oidiodendron 707.4774 -0.041568378 0.32905841
## Fusidium 439.4076 0.311219171 0.19138955
## Leptosphaeria 1215.8903 -0.911638026 0.44620438
## X.uncultured.eukaryote. 356.1635 -1.227915622 0.36919530
## Stemphylium 731.5821 0.838836467 0.41712173
## Trichoderma 1041.3259 0.006247107 0.30202328
## Fimicolochytrium 1001.5063 -0.111933140 0.19780177
## Volutella 318.0905 0.895861134 0.32804608
## X.uncultured.Monoblepharidales. 766.6738 0.631824602 0.19618789
## Chlamydomonas 251.2449 0.199145173 0.35607893
## Peziza 185.3868 0.892439184 0.17438466
## Delitschia 650.9164 1.070370873 0.76757682
## Cyberlindnera 415.7661 0.511003399 0.57754124
## Chrysosporium 2661.7691 0.402014214 0.45456357
## Neohelicomyces 494.1081 -0.296970544 0.51451954
## X.uncultured.Ichthyophonida. 857.5788 -0.655428134 0.47810120
## Coprinus 1265.6112 -0.973061109 0.29838891
## stat pvalue padj reject df
## Candida 0.75416394 0.4617067039 0.678980447 FALSE 16
## Mrakia -0.91249584 0.3750525626 0.599352818 FALSE 16
## Colletotrichum -1.63064692 0.1224895909 0.301119445 FALSE 16
## Cladosporium 3.96532633 0.0011100979 0.027752449 TRUE 16
## Sporobolomyces 5.14273811 0.0000982459 0.005165325 TRUE 16
## Juxtiphoma -0.02265647 0.9822044499 0.983753336 FALSE 16
## Sistotrema 0.09853745 0.9227294758 0.941560690 FALSE 16
## Gibellulopsis 0.15325080 0.8801166331 0.941560690 FALSE 16
## Botrytis 2.20480208 0.0424491117 0.161565743 FALSE 16
## Podospora -1.22254895 0.2392041635 0.449404417 FALSE 16
## Alternaria -0.64164121 0.5301917728 0.726290100 FALSE 16
## Fusarium -1.68766676 0.1108687504 0.291759869 FALSE 16
## Mortierella 0.73749856 0.4714973566 0.683329502 FALSE 16
## Cadophora -3.33559899 0.0041926729 0.048279840 TRUE 16
## Aspergillus 3.41450895 0.0035497969 0.048279840 TRUE 16
## Laetinaevia -1.02853699 0.3189960996 0.531660166 FALSE 16
## Paraphaeosphaeria -0.83000815 0.4187467500 0.624995149 FALSE 16
## Tetracladium -2.28367771 0.0363936161 0.161248995 FALSE 16
## Solicoccozyma 0.10771923 0.9155576367 0.941560690 FALSE 16
## Chloridium -2.52056924 0.0227135477 0.130447675 FALSE 16
## Trichosporiella -3.96776276 0.0011044220 0.027752449 TRUE 16
## Vishniacozyma 3.13231386 0.0064293598 0.052085622 FALSE 16
## Umbelopsis 1.55759562 0.1388868856 0.321515588 FALSE 16
## Plectosphaerella 2.27404759 0.0370872689 0.161248995 FALSE 16
## Tausonia -0.53169471 0.6022422554 0.747638543 FALSE 16
## Chordomyces 3.57686823 0.0025193717 0.048279840 TRUE 16
## Minimedusa 2.15003363 0.0471891164 0.168532559 FALSE 16
## Urceolella -2.75268581 0.0141556861 0.092522931 FALSE 16
## Naganishia 2.35264776 0.0317688567 0.161248995 FALSE 16
## Acremonium 1.59077023 0.1312232470 0.312436302 FALSE 16
## X.uncultured.fungus. 1.20115109 0.2471724292 0.449404417 FALSE 16
## Talaromyces 0.64344866 0.5290484274 0.726290100 FALSE 16
## Holtermanniella 1.04262910 0.3126186901 0.529862187 FALSE 16
## Sporidesmium -1.21175709 0.2431977675 0.449404417 FALSE 16
## Protoventuria -0.26074970 0.7976117872 0.896193019 FALSE 16
## Trichocladium -1.28941752 0.2155818993 0.431163799 FALSE 16
## Gorgomyces -3.31864698 0.0043451856 0.048279840 TRUE 16
## Papiliotrema 0.20364417 0.8411990793 0.934665644 FALSE 16
## Ophiosphaerella -0.59776349 0.5583643135 0.735978158 FALSE 16
## Pseudeurotium 1.09219907 0.2909190809 0.503485701 FALSE 16
## Coniochaeta -2.20233628 0.0426526860 0.161565743 FALSE 16
## Exophiala -1.29026085 0.2152961499 0.431163799 FALSE 16
## NA. 1.36347537 0.1916112153 0.399190032 FALSE 16
## Sakaguchia -1.54677514 0.1414668588 0.321515588 FALSE 16
## Pseudoanguillospora -0.18617880 0.8546445466 0.938813988 FALSE 16
## Halenospora -2.08351995 0.0535991518 0.175377167 FALSE 16
## Pleotrichocladium -1.50594208 0.1515685764 0.336819059 FALSE 16
## Cephalosporium -0.90639416 0.3781754133 0.599352818 FALSE 16
## X.uncultured.Spizellomycetales. -0.36481122 0.7200294433 0.827620050 FALSE 16
## Verticillium 2.05019474 0.0571018221 0.175377167 FALSE 16
## Pseudogymnoascus 0.71740147 0.4834694971 0.690670710 FALSE 16
## Devriesia 0.59626037 0.5593433999 0.735978158 FALSE 16
## Polymyxa -2.83710081 0.0118941512 0.084958223 FALSE 16
## Apodus 1.67047323 0.1142683480 0.292995764 FALSE 16
## Arthopyrenia 0.45272550 0.6568248570 0.801005923 FALSE 16
## Zasmidium 2.31072897 0.0345093512 0.161248995 FALSE 16
## X.uncultured.Agaricales. 0.37731123 0.7109001847 0.827620050 FALSE 16
## X.uncultured.Glomerales. 0.38749788 0.7034938563 0.827620050 FALSE 16
## Ochroconis -0.52675963 0.6055872198 0.747638543 FALSE 16
## X.uncultured.Basidiomycota. -0.37183848 0.7148916578 0.827620050 FALSE 16
## Microdochium 0.14643485 0.8854072592 0.941560690 FALSE 16
## X.uncultured.Hypocreales. -0.59781518 0.5583306590 0.735978158 FALSE 16
## X.uncultured.Mortierellales. 1.10325130 0.2862356512 0.503485701 FALSE 16
## X.uncultured.Ascomycota. 0.85241989 0.4065604066 0.616000616 FALSE 16
## Allovahlkampfia -0.36553144 0.7195022327 0.827620050 FALSE 16
## Rhodotorula 2.50408153 0.0234805815 0.130447675 FALSE 16
## Dioszegia 2.12546744 0.0494697626 0.170585388 FALSE 16
## Alpinaria 0.28402618 0.7800330469 0.886401190 FALSE 16
## Leucosporidium 2.27940802 0.0366996537 0.161248995 FALSE 16
## Trematosphaeria -3.10760544 0.0067711308 0.052085622 FALSE 16
## Paraphoma -1.08961615 0.2920217065 0.503485701 FALSE 16
## Neoascochyta 0.17443868 0.8637088687 0.938813988 FALSE 16
## Barnettozyma 1.26625110 0.2235490086 0.438331389 FALSE 16
## Apiotrichum 0.11299610 0.9114392608 0.941560690 FALSE 16
## Waitea 0.69760589 0.4954370238 0.697798625 FALSE 16
## Dendryphion -2.19073391 0.0436227506 0.161565743 FALSE 16
## Hyaloscypha -1.84299031 0.0839360597 0.226854215 FALSE 16
## Neopyrenochaeta -2.05407499 0.0566835155 0.175377167 FALSE 16
## Cladophialophora -2.19753371 0.0430517779 0.161565743 FALSE 16
## Nullicamyces 1.88524633 0.0776902616 0.221333203 FALSE 16
## Rhizophagus 1.87146684 0.0796799530 0.221333203 FALSE 16
## Spizellomyces -0.98445507 0.3395454644 0.556631909 FALSE 16
## Neohendersonia 1.22649160 0.2377578593 0.449404417 FALSE 16
## Oidiodendron -0.12632523 0.9010483201 0.941560690 FALSE 16
## Fusidium 1.62610328 0.1234589723 0.301119445 FALSE 16
## Leptosphaeria -2.04309522 0.0578744652 0.175377167 FALSE 16
## X.uncultured.eukaryote. -3.32592430 0.0042790512 0.048279840 TRUE 16
## Stemphylium 2.01101121 0.0614860981 0.180841465 FALSE 16
## Trichoderma 0.02068419 0.9837533355 0.983753336 FALSE 16
## Fimicolochytrium -0.56588543 0.5793223568 0.738886328 FALSE 16
## Volutella 2.73090033 0.0148036690 0.092522931 FALSE 16
## X.uncultured.Monoblepharidales. 3.22050773 0.0053423642 0.048566947 TRUE 16
## Chlamydomonas 0.55927255 0.5837201991 0.738886328 FALSE 16
## Peziza 5.11764731 0.0001033065 0.005165325 TRUE 16
## Delitschia 1.39448046 0.1822344813 0.396161916 FALSE 16
## Cyberlindnera 0.88479119 0.3893724699 0.599352818 FALSE 16
## Chrysosporium 0.88439602 0.3895793318 0.599352818 FALSE 16
## Neohelicomyces -0.57718031 0.5718504168 0.738886328 FALSE 16
## X.uncultured.Ichthyophonida. -1.37089832 0.1893315960 0.399190032 FALSE 16
## Coprinus -3.26104985 0.0049055962 0.048566947 TRUE 16
##
##
## $covariance
## NULL
##
## $feature.dat.use
## 1 2 3
## Candida 3.232412e-01 2.575758e-01 7.743115e-02
## Mrakia 9.112224e-02 6.456154e-02 2.026302e-01
## Colletotrichum 7.123106e-03 1.790024e-02 1.126378e-02
## Cladosporium 7.182996e-02 2.651515e-02 9.435631e-03
## Sporobolomyces 1.236031e-02 4.176723e-02 2.034558e-03
## Juxtiphoma 3.808759e-02 2.862698e-02 3.824379e-02
## Sistotrema 5.974999e-02 5.390185e-02 4.393466e-02
## Gibellulopsis 1.729169e-02 1.505095e-02 3.190423e-02
## Botrytis 8.257196e-03 1.146420e-02 5.278056e-03
## Podospora 5.186233e-03 4.592384e-03 6.988264e-03
## Alternaria 9.480485e-03 8.950121e-03 1.627646e-02
## Fusarium 1.197803e-02 1.759855e-02 2.002123e-02
## Mortierella 3.706819e-02 3.955484e-02 9.211535e-02
## Cadophora 1.279356e-02 1.065969e-02 3.096067e-02
## Aspergillus 1.634874e-02 1.541968e-02 1.559828e-02
## Laetinaevia 6.027244e-03 4.022526e-03 8.845904e-03
## Paraphaeosphaeria 7.645552e-03 5.933226e-03 8.108746e-03
## Tetracladium 7.084878e-03 4.223652e-03 2.046353e-02
## Solicoccozyma 1.590275e-02 8.782515e-03 2.633131e-02
## Chloridium 9.926475e-03 2.336417e-02 3.249396e-02
## Trichosporiella 6.944710e-03 3.620274e-03 4.968450e-02
## Vishniacozyma 5.810620e-03 2.353178e-02 2.712744e-03
## Umbelopsis 1.224563e-02 1.008984e-02 2.146606e-02
## Plectosphaerella 5.632223e-03 5.095200e-03 1.710208e-03
## Tausonia 5.504798e-03 4.424779e-03 9.818954e-03
## Chordomyces 5.976273e-03 1.672700e-02 5.012679e-04
## Minimedusa 1.178689e-02 7.978010e-03 1.379961e-02
## Urceolella 6.065471e-03 7.978010e-03 1.851743e-02
## Naganishia 4.574589e-03 6.167873e-03 4.275520e-03
## Acremonium 9.149177e-03 1.421293e-02 5.396002e-03
## X.uncultured.fungus. 1.078023e-02 2.269375e-02 1.783924e-02
## Talaromyces 3.415013e-03 8.380263e-04 4.069116e-03
## Holtermanniella 3.415013e-03 2.614642e-03 4.098602e-03
## Sporidesmium 5.020579e-03 2.849289e-03 6.781860e-03
## Protoventuria 9.939218e-04 2.815768e-03 1.916613e-03
## Trichocladium 3.313073e-03 3.050416e-03 7.312614e-03
## Gorgomyces 1.656536e-04 4.357737e-04 4.629357e-03
## Papiliotrema 5.453827e-03 3.184500e-03 4.481925e-03
## Ophiosphaerella 1.822190e-03 1.743095e-03 2.388394e-03
## Pseudeurotium 2.803369e-03 1.106195e-03 3.066580e-03
## Coniochaeta 2.089784e-03 9.050684e-04 5.219084e-03
## Exophiala 6.001758e-03 2.111826e-03 7.577991e-03
## NA. 5.058807e-03 5.564495e-03 3.626821e-03
## Sakaguchia 8.282682e-04 1.005632e-03 1.533290e-03
## Pseudoanguillospora 2.293666e-03 8.715473e-04 6.192133e-04
## Halenospora 6.753571e-04 1.106195e-03 3.096067e-03
## Pleotrichocladium 5.734164e-04 1.005632e-03 1.769181e-03
## Cephalosporium 7.518126e-04 1.139716e-03 2.358908e-03
## X.uncultured.Spizellomycetales. 2.803369e-04 1.541968e-03 2.388394e-03
## Verticillium 4.077628e-03 4.123089e-03 9.435631e-04
## Pseudogymnoascus 6.880997e-04 5.698579e-04 7.371587e-04
## Devriesia 8.664959e-04 1.173237e-03 1.946099e-03
## Polymyxa 4.842183e-04 4.022526e-04 1.592263e-03
## Apodus 1.567338e-03 1.910700e-03 3.243498e-04
## Arthopyrenia 9.811792e-04 1.139716e-03 2.123017e-03
## Zasmidium 8.664959e-04 8.380263e-04 4.422952e-04
## X.uncultured.Agaricales. 8.282682e-04 8.380263e-04 8.845904e-05
## X.uncultured.Glomerales. 1.924131e-03 7.374631e-04 1.356372e-03
## Ochroconis 4.969609e-04 2.681684e-04 8.551041e-04
## X.uncultured.Basidiomycota. 1.019407e-03 9.050684e-04 1.326886e-03
## Microdochium 3.185647e-04 7.709842e-04 2.948635e-04
## X.uncultured.Hypocreales. 9.811792e-04 7.039421e-04 1.710208e-03
## X.uncultured.Mortierellales. 1.146833e-03 7.374631e-04 3.833225e-04
## X.uncultured.Ascomycota. 2.930795e-04 1.877179e-03 3.538362e-04
## Allovahlkampfia 2.930795e-04 1.676053e-04 4.717816e-04
## Rhodotorula 5.479312e-04 5.665058e-03 2.739656e-04
## Dioszegia 1.057635e-03 2.044784e-03 2.064044e-04
## Alpinaria 3.389528e-03 3.184500e-03 7.371587e-04
## Leucosporidium 8.282682e-04 4.123089e-03 7.666450e-04
## Trematosphaeria 4.587331e-04 1.411273e-04 2.034558e-03
## Paraphoma 6.626145e-04 1.518504e-02 4.039630e-03
## Neoascochyta 5.097035e-03 1.863770e-02 3.243498e-03
## Barnettozyma 1.745734e-03 1.803433e-02 1.032022e-03
## Apiotrichum 1.376199e-03 7.374631e-04 2.299935e-03
## Waitea 6.243868e-04 9.888710e-03 1.179454e-03
## Dendryphion 1.540642e-04 1.005632e-03 1.651235e-03
## Hyaloscypha 6.753571e-04 5.698579e-04 7.666450e-04
## Neopyrenochaeta 1.656536e-04 6.369000e-04 1.798667e-03
## Cladophialophora 1.121348e-03 2.388858e-04 3.155039e-03
## Nullicamyces 1.656536e-03 1.642532e-03 2.121168e-04
## Rhizophagus 4.205054e-04 3.352105e-04 1.769181e-04
## Spizellomyces 4.842183e-04 1.461134e-04 1.385858e-03
## Neohendersonia 7.390700e-04 1.005632e-03 7.666450e-04
## Oidiodendron 1.401685e-03 2.346474e-04 1.179454e-03
## Fusidium 2.421092e-04 2.681684e-04 8.361004e-05
## Leptosphaeria 1.656536e-04 6.369000e-04 1.680722e-03
## X.uncultured.eukaryote. 2.293666e-04 2.011263e-04 3.862712e-03
## Stemphylium 1.911388e-04 7.136740e-05 1.474317e-04
## Trichoderma 1.363457e-03 1.550084e-04 6.486997e-04
## Fimicolochytrium 6.371294e-04 2.616805e-04 8.845904e-04
## Volutella 6.116442e-04 3.251542e-03 3.917697e-05
## X.uncultured.Monoblepharidales. 5.097035e-04 1.039153e-03 7.076723e-04
## Chlamydomonas 6.371294e-05 5.698579e-04 2.358908e-04
## Peziza 2.293666e-04 1.340842e-04 3.361571e-05
## Delitschia 1.340554e-05 3.687316e-04 1.340554e-05
## Cyberlindnera 1.302292e-02 3.486189e-03 2.653771e-04
## Chrysosporium 8.231711e-03 6.804773e-03 1.828154e-03
## Neohelicomyces 3.567924e-04 6.369000e-04 2.358908e-04
## X.uncultured.Ichthyophonida. 2.930795e-04 6.391138e-05 3.774253e-03
## Coprinus 5.097035e-04 1.704303e-04 2.683258e-03
## 4 5 6
## Candida 2.805780e-02 5.264330e-02 1.998296e-02
## Mrakia 1.349000e-01 1.626853e-01 9.759267e-02
## Colletotrichum 1.288943e-01 1.956231e-03 5.112910e-03
## Cladosporium 2.543032e-02 4.009479e-02 1.565829e-01
## Sporobolomyces 3.780364e-03 2.772123e-02 9.614401e-02
## Juxtiphoma 7.752426e-02 6.091354e-02 2.381764e-02
## Sistotrema 3.524318e-02 1.359819e-02 5.372816e-02
## Gibellulopsis 2.516221e-02 5.342261e-02 1.246272e-02
## Botrytis 4.678535e-03 2.407914e-02 1.785258e-02
## Podospora 6.153145e-03 3.308098e-03 6.753302e-03
## Alternaria 2.839294e-02 3.093390e-02 2.699190e-02
## Fusarium 2.048367e-02 2.260004e-02 4.793353e-03
## Mortierella 5.001609e-02 7.137859e-02 6.766084e-02
## Cadophora 2.962625e-02 1.245308e-02 1.369834e-02
## Aspergillus 1.556384e-02 2.072333e-02 1.670217e-02
## Laetinaevia 1.979999e-02 7.156944e-03 3.067746e-03
## Paraphaeosphaeria 2.258834e-02 1.529996e-02 7.413720e-03
## Tetracladium 3.154325e-02 1.269165e-02 8.947593e-03
## Solicoccozyma 2.092606e-02 2.390419e-02 2.030251e-02
## Chloridium 2.943858e-02 1.596794e-02 1.938645e-02
## Trichosporiella 3.545767e-02 1.205547e-02 6.497657e-03
## Vishniacozyma 6.970883e-03 3.058401e-02 3.003835e-02
## Umbelopsis 7.198777e-03 2.255233e-02 1.991905e-02
## Plectosphaerella 4.102097e-03 5.773268e-03 2.236898e-03
## Tausonia 1.422328e-02 1.458426e-02 6.902429e-03
## Chordomyces 3.887608e-04 3.514855e-03 9.586706e-04
## Minimedusa 4.986863e-03 9.701635e-03 1.301662e-02
## Urceolella 1.132769e-02 6.170876e-03 8.990200e-03
## Naganishia 3.941230e-03 7.999873e-03 1.205795e-02
## Acremonium 2.225320e-03 3.260386e-03 6.305922e-03
## X.uncultured.fungus. 8.874470e-03 1.059228e-02 9.544099e-03
## Talaromyces 1.863371e-03 3.737515e-03 4.686834e-03
## Holtermanniella 3.472036e-03 5.471086e-03 2.876012e-03
## Sporidesmium 4.477452e-03 1.669954e-03 5.048999e-03
## Protoventuria 3.740147e-03 1.431389e-03 1.597784e-03
## Trichocladium 3.324575e-03 4.151027e-03 1.896037e-03
## Gorgomyces 4.825996e-04 7.793117e-04 1.917341e-04
## Papiliotrema 3.203925e-03 5.121191e-03 4.154239e-03
## Ophiosphaerella 2.895598e-03 1.797188e-03 2.258202e-03
## Pseudeurotium 1.246716e-03 7.793117e-04 3.451214e-03
## Coniochaeta 6.528500e-03 2.242509e-03 2.023860e-03
## Exophiala 9.745831e-03 2.608308e-03 6.668087e-03
## NA. 3.994852e-03 4.325975e-03 1.035364e-02
## Sakaguchia 6.166550e-04 6.997901e-04 1.193012e-03
## Pseudoanguillospora 1.327149e-03 7.156944e-04 1.917341e-04
## Halenospora 3.163709e-03 1.654049e-03 5.965062e-04
## Pleotrichocladium 3.981447e-03 2.306126e-03 1.320835e-03
## Cephalosporium 1.635476e-03 2.560595e-03 7.882403e-04
## X.uncultured.Spizellomycetales. 1.702504e-03 4.453209e-03 2.045164e-03
## Verticillium 1.152877e-03 2.417457e-03 8.521517e-04
## Pseudogymnoascus 4.289774e-04 7.793117e-04 9.586706e-04
## Devriesia 2.037643e-03 2.083466e-03 1.896037e-03
## Polymyxa 4.021663e-04 3.180864e-04 5.112910e-04
## Apodus 2.386187e-03 4.612253e-04 1.022582e-03
## Arthopyrenia 1.246716e-03 8.588333e-04 1.427354e-03
## Zasmidium 1.260121e-03 4.612253e-04 7.030251e-04
## X.uncultured.Agaricales. 4.772374e-03 6.202685e-04 1.193012e-03
## X.uncultured.Glomerales. 1.273527e-03 7.634073e-04 2.556455e-04
## Ochroconis 9.517937e-04 1.256441e-03 4.686834e-04
## X.uncultured.Basidiomycota. 5.228162e-04 4.930339e-04 4.686834e-04
## Microdochium 6.702772e-04 3.657994e-04 4.686834e-04
## X.uncultured.Hypocreales. 8.579549e-04 2.385648e-04 9.373669e-04
## X.uncultured.Mortierellales. 3.083275e-04 2.226605e-04 1.150405e-03
## X.uncultured.Ascomycota. 1.420988e-03 1.161015e-03 7.669365e-04
## Allovahlkampfia 2.681109e-04 1.161015e-03 2.130379e-04
## Rhodotorula 1.112660e-03 3.912463e-03 4.546229e-02
## Dioszegia 4.758968e-03 2.290222e-03 6.327226e-03
## Alpinaria 6.702772e-04 3.319232e-02 3.621645e-04
## Leucosporidium 1.251849e-04 1.431389e-03 1.043886e-03
## Trematosphaeria 2.667703e-03 1.001972e-03 7.669365e-04
## Paraphoma 1.206499e-03 1.272346e-04 1.299531e-03
## Neoascochyta 1.193093e-03 1.288250e-03 7.243289e-04
## Barnettozyma 1.479458e-04 2.799160e-03 1.171709e-03
## Apiotrichum 7.238994e-04 4.787200e-03 2.130379e-04
## Waitea 3.190520e-03 5.248425e-04 1.363443e-03
## Dendryphion 1.984021e-03 6.361728e-04 6.391138e-04
## Hyaloscypha 1.809749e-03 6.520771e-04 2.982531e-04
## Neopyrenochaeta 8.043327e-04 4.135123e-04 8.947593e-04
## Cladophialophora 1.300338e-03 8.270246e-04 8.308479e-04
## Nullicamyces 1.313743e-03 6.043641e-04 1.278228e-03
## Rhizophagus 1.916993e-03 1.590432e-04 2.428632e-03
## Spizellomyces 8.445493e-04 8.588333e-04 1.278228e-03
## Neohendersonia 9.517937e-04 7.634073e-04 3.621645e-04
## Oidiodendron 9.383881e-05 5.566512e-04 4.260758e-04
## Fusidium 4.021663e-04 1.908518e-04 3.195569e-04
## Leptosphaeria 2.748137e-03 3.498950e-04 8.521517e-04
## X.uncultured.eukaryote. 1.206499e-03 2.862778e-04 4.260758e-05
## Stemphylium 1.152877e-03 2.465170e-03 2.982531e-04
## Trichoderma 9.249826e-04 6.043641e-04 1.746911e-03
## Fimicolochytrium 7.104939e-04 9.224505e-04 7.030251e-04
## Volutella 1.608665e-04 3.180864e-04 1.917341e-04
## X.uncultured.Monoblepharidales. 5.630329e-04 6.838857e-04 1.427354e-03
## Chlamydomonas 6.702772e-05 3.657994e-04 3.185647e-05
## Peziza 1.206499e-04 4.135123e-04 8.521517e-05
## Delitschia 2.681109e-05 7.156944e-04 1.695782e-02
## Cyberlindnera 5.362218e-05 8.111203e-04 2.681109e-05
## Chrysosporium 5.496273e-04 2.748137e-04 4.942480e-03
## Neohelicomyces 4.960051e-04 6.361728e-05 3.180864e-05
## X.uncultured.Ichthyophonida. 2.547053e-04 1.272346e-03 1.278228e-04
## Coprinus 3.016248e-03 4.135123e-04 3.408607e-04
## 7 8 9
## Candida 6.361909e-02 4.021124e-02 1.701996e-02
## Mrakia 1.363809e-01 1.351605e-01 1.407039e-01
## Colletotrichum 9.966216e-03 6.707097e-03 1.103616e-02
## Cladosporium 1.334459e-02 5.359410e-03 3.401169e-02
## Sporobolomyces 1.900338e-03 1.457383e-03 5.955573e-03
## Juxtiphoma 4.691723e-02 4.049332e-02 4.626154e-02
## Sistotrema 3.086993e-02 4.466175e-02 6.102346e-02
## Gibellulopsis 3.593750e-02 1.869525e-02 2.133845e-02
## Botrytis 2.871622e-03 6.158620e-03 5.173728e-02
## Podospora 2.286740e-02 1.750427e-02 3.415281e-03
## Alternaria 3.203125e-02 3.184304e-02 2.610856e-02
## Fusarium 6.528716e-02 6.526883e-02 1.608852e-02
## Mortierella 7.060811e-02 7.940388e-02 1.099664e-01
## Cadophora 1.910895e-02 2.783132e-02 1.572158e-02
## Aspergillus 1.982686e-02 1.317913e-02 1.803607e-02
## Laetinaevia 6.841216e-03 1.283438e-02 6.181377e-03
## Paraphaeosphaeria 2.588682e-02 1.968251e-02 1.069745e-02
## Tetracladium 2.685811e-02 1.957281e-02 3.014480e-02
## Solicoccozyma 2.398649e-02 2.040337e-02 2.958029e-02
## Chloridium 3.274916e-02 7.094166e-02 1.673770e-02
## Trichosporiella 3.317145e-02 4.693401e-02 1.227808e-02
## Vishniacozyma 2.787162e-03 6.299657e-03 4.120918e-03
## Umbelopsis 2.217061e-02 1.914970e-02 2.613678e-02
## Plectosphaerella 1.815878e-03 1.551408e-03 2.229812e-03
## Tausonia 1.203547e-02 1.018601e-02 8.382963e-03
## Chordomyces 9.290541e-04 3.447573e-04 1.044342e-03
## Minimedusa 3.462838e-03 3.400561e-03 1.171357e-02
## Urceolella 1.651182e-02 1.847586e-02 1.591916e-02
## Naganishia 4.032939e-03 3.494586e-03 2.963674e-03
## Acremonium 6.989020e-03 4.904957e-03 5.475740e-03
## X.uncultured.fungus. 1.184544e-02 9.355460e-03 9.907138e-03
## Talaromyces 8.889358e-03 2.805071e-03 4.628976e-03
## Holtermanniella 3.272804e-03 2.664034e-03 1.637077e-03
## Sporidesmium 3.483953e-03 5.547459e-03 5.927348e-03
## Protoventuria 2.385980e-03 4.528858e-03 3.133027e-03
## Trichocladium 6.228885e-03 2.209581e-03 5.024133e-03
## Gorgomyces 7.369088e-03 4.152759e-03 1.072568e-03
## Papiliotrema 4.624155e-03 6.205632e-03 1.891106e-03
## Ophiosphaerella 2.934966e-03 3.760989e-03 2.229812e-03
## Pseudeurotium 1.393581e-03 1.112626e-03 2.173361e-03
## Coniochaeta 5.067568e-03 2.225252e-03 2.173361e-03
## Exophiala 4.983108e-03 9.010703e-03 5.757995e-03
## NA. 6.355574e-03 5.422093e-03 4.798329e-03
## Sakaguchia 1.625845e-03 4.622882e-03 3.669310e-04
## Pseudoanguillospora 4.645270e-04 7.992102e-04 1.693528e-04
## Halenospora 2.554899e-03 1.990190e-03 8.185385e-04
## Pleotrichocladium 2.449324e-03 2.319277e-03 1.608852e-03
## Cephalosporium 2.766047e-03 2.099886e-03 2.455615e-03
## X.uncultured.Spizellomycetales. 1.942568e-03 3.290865e-03 2.794321e-03
## Verticillium 1.435811e-03 1.190980e-03 1.580626e-03
## Pseudogymnoascus 6.967905e-04 9.715889e-04 1.749979e-03
## Devriesia 2.217061e-03 2.679705e-03 2.963674e-03
## Polymyxa 2.956081e-03 1.285005e-03 1.298371e-03
## Apodus 4.222973e-04 6.111607e-04 5.645093e-04
## Arthopyrenia 1.097973e-03 1.128297e-03 1.608852e-03
## Zasmidium 5.912162e-04 7.365270e-04 5.927348e-04
## X.uncultured.Agaricales. 1.140203e-03 5.641484e-04 2.822547e-03
## X.uncultured.Glomerales. 6.123311e-04 4.387821e-04 7.338621e-04
## Ochroconis 1.731419e-03 8.618933e-04 9.596658e-04
## X.uncultured.Basidiomycota. 6.334459e-04 1.629762e-03 7.338621e-04
## Microdochium 1.478041e-04 1.520066e-03 6.491857e-04
## X.uncultured.Hypocreales. 9.079392e-04 1.911836e-03 2.766096e-03
## X.uncultured.Mortierellales. 3.378378e-04 9.402473e-05 1.552401e-03
## X.uncultured.Ascomycota. 6.123311e-04 6.111607e-04 4.798329e-04
## Allovahlkampfia 1.309122e-03 1.426042e-03 7.620876e-04
## Rhodotorula 9.079392e-04 1.582750e-03 1.806430e-03
## Dioszegia 1.858108e-03 1.032022e-04 4.233820e-04
## Alpinaria 2.343750e-03 2.397631e-03 5.927348e-04
## Leucosporidium 1.520270e-03 4.387821e-04 1.213695e-03
## Trematosphaeria 2.850507e-03 1.968251e-02 2.822547e-04
## Paraphoma 4.961993e-03 3.243853e-03 3.245928e-03
## Neoascochyta 3.652872e-03 9.559181e-04 9.032149e-04
## Barnettozyma 1.135980e-02 3.604281e-04 1.411273e-03
## Apiotrichum 3.103885e-03 3.290865e-04 6.209602e-04
## Waitea 4.011824e-04 4.701236e-04 2.540292e-04
## Dendryphion 2.048142e-03 1.190980e-03 1.241920e-03
## Hyaloscypha 4.687500e-03 2.131227e-03 3.330605e-03
## Neopyrenochaeta 1.245777e-03 2.805071e-03 3.387056e-04
## Cladophialophora 1.710304e-03 2.899096e-03 1.383048e-03
## Nullicamyces 6.967905e-04 4.387821e-04 5.927348e-04
## Rhizophagus 6.828269e-05 2.037202e-04 4.657202e-03
## Spizellomyces 5.067568e-04 7.521978e-04 2.907223e-03
## Neohendersonia 7.812500e-04 1.081284e-03 1.129019e-03
## Oidiodendron 7.390203e-04 8.148810e-04 1.552401e-03
## Fusidium 2.111486e-04 2.193910e-04 4.798329e-04
## Leptosphaeria 2.681588e-03 5.735508e-03 1.665302e-03
## X.uncultured.eukaryote. 1.393581e-03 2.820742e-04 8.185385e-04
## Stemphylium 7.136740e-05 2.507326e-04 1.129019e-03
## Trichoderma 8.445946e-04 1.206651e-03 1.185470e-03
## Fimicolochytrium 1.140203e-03 1.833482e-03 1.270146e-03
## Volutella 1.689189e-04 7.835394e-05 3.387056e-04
## X.uncultured.Monoblepharidales. 2.744932e-04 1.372466e-04 7.056366e-04
## Chlamydomonas 1.055743e-04 3.134158e-04 4.798329e-04
## Peziza 3.361571e-05 1.410371e-04 2.540292e-04
## Delitschia 9.712838e-04 4.544529e-03 7.959581e-03
## Cyberlindnera 5.067568e-04 4.544529e-04 3.951565e-04
## Chrysosporium 2.491554e-03 1.206651e-03 3.189478e-03
## Neohelicomyces 7.390203e-04 8.305518e-04 3.180864e-05
## X.uncultured.Ichthyophonida. 2.618243e-03 3.212512e-03 2.681419e-03
## Coprinus 5.236486e-03 2.225252e-03 1.100793e-03
## 10 11 12
## Candida 1.779902e-02 4.037171e-02 3.993721e-02
## Mrakia 8.027768e-02 1.128019e-01 1.216132e-01
## Colletotrichum 3.068169e-02 2.460524e-03 1.444803e-03
## Cladosporium 4.536247e-02 6.684026e-02 3.132191e-02
## Sporobolomyces 1.356549e-02 2.704188e-02 1.257514e-02
## Juxtiphoma 8.665073e-02 8.623779e-02 4.955140e-02
## Sistotrema 2.936156e-02 9.746542e-03 1.023848e-02
## Gibellulopsis 1.843633e-02 4.082559e-02 4.955140e-02
## Botrytis 5.870035e-02 3.244070e-02 5.012218e-03
## Podospora 6.304768e-03 2.221638e-03 6.135954e-03
## Alternaria 8.214408e-02 3.571343e-02 1.669550e-02
## Fusarium 2.626607e-02 4.304723e-02 3.865294e-02
## Mortierella 7.017184e-02 6.282697e-02 1.284448e-01
## Cadophora 2.993058e-02 1.414204e-02 2.192177e-02
## Aspergillus 1.131217e-02 1.595757e-02 2.286713e-02
## Laetinaevia 2.897462e-02 2.195361e-02 7.491572e-03
## Paraphaeosphaeria 1.067486e-02 1.748644e-02 2.042345e-02
## Tetracladium 4.197109e-02 2.195361e-02 1.967429e-02
## Solicoccozyma 2.014339e-02 2.226416e-02 2.894957e-02
## Chloridium 2.023444e-02 1.889587e-02 2.272444e-02
## Trichosporiella 1.666098e-02 2.195361e-02 1.496531e-02
## Vishniacozyma 2.053033e-02 2.601467e-02 1.448371e-02
## Umbelopsis 5.121202e-03 1.151430e-02 3.610224e-02
## Plectosphaerella 2.754069e-03 8.074341e-03 2.675561e-03
## Tausonia 1.684306e-02 2.350637e-02 1.275351e-02
## Chordomyces 1.206328e-03 2.102195e-03 2.586376e-03
## Minimedusa 6.190964e-03 3.153293e-03 9.614184e-03
## Urceolella 9.514055e-03 3.846062e-03 9.774718e-03
## Naganishia 2.458177e-03 5.470486e-03 6.849437e-03
## Acremonium 2.503699e-03 2.818853e-03 4.209550e-03
## X.uncultured.fungus. 8.740184e-03 6.593249e-03 1.298539e-02
## Talaromyces 3.414135e-04 1.146652e-03 3.317696e-03
## Holtermanniella 3.527939e-03 9.459879e-03 5.654353e-03
## Sporidesmium 4.028679e-03 1.791644e-03 2.051264e-03
## Protoventuria 1.934676e-03 2.102195e-03 2.176123e-03
## Trichocladium 4.210766e-03 2.149973e-03 6.528370e-03
## Gorgomyces 9.331968e-04 9.555433e-04 6.956460e-04
## Papiliotrema 2.822351e-03 2.078307e-03 5.297612e-03
## Ophiosphaerella 4.415614e-03 2.149973e-03 6.207302e-03
## Pseudeurotium 2.048481e-04 3.344402e-04 2.140449e-03
## Coniochaeta 1.866394e-03 1.146652e-03 2.354494e-03
## Exophiala 8.603619e-03 4.514942e-03 6.688904e-03
## NA. 3.550700e-03 2.556078e-03 5.957583e-03
## Sakaguchia 7.283487e-04 5.972146e-04 7.491572e-04
## Pseudoanguillospora 1.001479e-03 1.003321e-03 5.707864e-04
## Halenospora 2.503699e-03 2.412747e-03 4.138202e-03
## Pleotrichocladium 3.391374e-03 2.078307e-03 4.066853e-03
## Cephalosporium 2.549220e-03 3.869951e-03 1.819382e-03
## X.uncultured.Spizellomycetales. 1.320132e-03 1.242206e-03 4.494943e-03
## Verticillium 2.731308e-03 3.392179e-03 2.211797e-03
## Pseudogymnoascus 1.024240e-03 2.866630e-04 1.212921e-03
## Devriesia 9.559577e-04 1.982752e-03 3.282022e-03
## Polymyxa 1.092523e-03 7.166575e-04 9.275280e-04
## Apodus 1.342893e-03 2.388858e-04 7.491572e-04
## Arthopyrenia 4.779788e-04 6.211032e-04 1.962078e-03
## Zasmidium 5.462615e-04 5.733260e-04 1.516151e-03
## X.uncultured.Agaricales. 1.866394e-03 4.538831e-04 7.491572e-04
## X.uncultured.Glomerales. 9.559577e-04 4.299945e-04 1.105899e-03
## Ochroconis 2.503699e-04 6.927689e-04 9.988763e-04
## X.uncultured.Basidiomycota. 1.001479e-03 6.449918e-04 1.284269e-03
## Microdochium 1.160806e-03 5.016603e-04 6.599718e-04
## X.uncultured.Hypocreales. 8.876750e-04 4.538831e-04 7.491572e-04
## X.uncultured.Mortierellales. 5.462615e-04 7.166575e-05 1.962078e-04
## X.uncultured.Ascomycota. 1.229088e-03 3.822173e-04 1.302107e-03
## Allovahlkampfia 2.731308e-04 2.149973e-04 1.088062e-03
## Rhodotorula 1.060658e-02 5.398820e-03 4.494943e-03
## Dioszegia 1.411176e-03 3.944005e-02 4.280898e-04
## Alpinaria 7.966314e-04 1.672201e-04 1.275351e-02
## Leucosporidium 2.503699e-04 1.552758e-03 1.266432e-03
## Trematosphaeria 1.889154e-03 1.600535e-03 2.033427e-03
## Paraphoma 2.731308e-03 1.194429e-02 6.361728e-05
## Neoascochyta 5.462615e-04 3.822173e-04 3.014466e-03
## Barnettozyma 2.958917e-04 1.409426e-03 1.551826e-03
## Apiotrichum 1.024240e-03 8.074341e-03 7.331038e-03
## Waitea 6.373051e-04 4.538831e-04 1.270146e-04
## Dendryphion 5.030158e-03 1.242206e-03 1.266432e-03
## Hyaloscypha 3.801070e-03 6.211032e-04 8.383426e-04
## Neopyrenochaeta 8.649141e-04 6.449918e-04 8.282682e-05
## Cladophialophora 1.638785e-03 4.777717e-04 2.532865e-03
## Nullicamyces 9.104359e-04 5.494374e-04 4.994381e-04
## Rhizophagus 1.365654e-04 2.388858e-04 8.026684e-04
## Spizellomyces 1.934676e-03 3.822173e-04 1.373455e-03
## Neohendersonia 5.007397e-04 5.255488e-04 2.211797e-03
## Oidiodendron 2.731308e-04 4.691941e-05 5.172752e-04
## Fusidium 8.876750e-04 1.672201e-04 4.816011e-04
## Leptosphaeria 3.778309e-03 5.016603e-04 5.886235e-04
## X.uncultured.eukaryote. 4.324570e-04 2.130379e-05 6.064606e-04
## Stemphylium 3.573461e-03 3.153293e-03 6.599718e-04
## Trichoderma 7.283487e-04 4.061059e-04 5.707864e-04
## Fimicolochytrium 7.283487e-04 6.688803e-04 8.205055e-04
## Volutella 1.820872e-04 5.255488e-04 3.032303e-04
## X.uncultured.Monoblepharidales. 1.372466e-04 5.733260e-04 1.462640e-03
## Chlamydomonas 4.552179e-04 5.733260e-04 5.172752e-04
## Peziza 6.828269e-05 2.388858e-04 2.853932e-04
## Delitschia 1.340554e-05 4.538831e-04 1.048820e-02
## Cyberlindnera 1.593263e-04 2.149973e-04 5.172752e-04
## Chrysosporium 6.828269e-04 2.748137e-04 2.748137e-04
## Neohelicomyces 4.324570e-04 3.105516e-04 2.069101e-03
## X.uncultured.Ichthyophonida. 1.820872e-04 6.391138e-05 3.103651e-03
## Coprinus 1.934676e-03 8.361004e-04 3.817134e-03
## 13 14 15
## Candida 0.0251802065 0.0582199385 5.860949e-02
## Mrakia 0.1039109682 0.1205157484 1.066295e-01
## Colletotrichum 0.0062828755 0.0053129064 6.477720e-03
## Cladosporium 0.0294174946 0.0087385416 4.741625e-02
## Sporobolomyces 0.0367962205 0.0013480509 4.474032e-02
## Juxtiphoma 0.0298801870 0.0676245758 5.085907e-02
## Sistotrema 0.1560734463 0.0487042852 2.586193e-02
## Gibellulopsis 0.0253993766 0.0365242491 3.284546e-02
## Botrytis 0.0222092344 0.0132426174 3.441187e-02
## Podospora 0.0068673290 0.0054715006 7.424087e-03
## Alternaria 0.0270066238 0.0198718559 2.925580e-02
## Fusarium 0.0064289889 0.0221714721 1.605561e-02
## Mortierella 0.1130187025 0.0787578901 8.499355e-02
## Cadophora 0.0148792129 0.0201731849 1.641457e-02
## Aspergillus 0.0206993961 0.0233450693 2.352864e-02
## Laetinaevia 0.0043103448 0.0146541060 9.218921e-03
## Paraphaeosphaeria 0.0144895772 0.0288324293 1.664301e-02
## Tetracladium 0.0113968440 0.0322897834 2.377339e-02
## Solicoccozyma 0.0228910968 0.0272623466 3.654935e-02
## Chloridium 0.0161698812 0.0370000317 2.398551e-02
## Trichosporiella 0.0100331190 0.0283725061 2.507873e-02
## Vishniacozyma 0.0217708942 0.0172074730 2.082008e-02
## Umbelopsis 0.0283947010 0.0173026295 3.220911e-02
## Plectosphaerella 0.0008279758 0.0019665683 1.811151e-03
## Tausonia 0.0075735437 0.0131474609 1.413024e-02
## Chordomyces 0.0008279758 0.0012846132 9.463671e-04
## Minimedusa 0.0183128775 0.0075966632 6.738786e-03
## Urceolella 0.0162185856 0.0168268468 1.168274e-02
## Naganishia 0.0037015391 0.0041393092 8.142020e-03
## Acremonium 0.0057714787 0.0035049323 4.046535e-03
## X.uncultured.fungus. 0.0150009741 0.0128619913 1.173169e-02
## Talaromyces 0.0072082603 0.0012053161 2.137484e-03
## Holtermanniella 0.0026056887 0.0037428236 8.207287e-03
## Sporidesmium 0.0052844341 0.0076601009 3.638618e-03
## Protoventuria 0.0026543931 0.0025533670 1.240067e-03
## Trichocladium 0.0036771868 0.0072636153 3.899685e-03
## Gorgomyces 0.0012906682 0.0006660957 1.631667e-04
## Papiliotrema 0.0030927333 0.0039014178 8.223604e-03
## Ophiosphaerella 0.0038476524 0.0027119612 2.480134e-03
## Pseudeurotium 0.0055279564 0.0007453928 9.953171e-04
## Coniochaeta 0.0027030976 0.0023947727 1.158484e-03
## Exophiala 0.0069160335 0.0092619025 4.128119e-03
## NA. 0.0079875317 0.0083737749 6.853003e-03
## Sakaguchia 0.0009740892 0.0006978146 1.337967e-03
## Pseudoanguillospora 0.0002435223 0.0042027469 1.044267e-03
## Halenospora 0.0010714981 0.0031560250 1.713251e-03
## Pleotrichocladium 0.0006331580 0.0041075903 3.410185e-03
## Cephalosporium 0.0018020651 0.0018079741 1.517451e-03
## X.uncultured.Spizellomycetales. 0.0001461134 0.0006185175 2.839101e-03
## Verticillium 0.0008279758 0.0027436800 1.191117e-03
## Pseudogymnoascus 0.0010471459 0.0008564088 2.937001e-04
## Devriesia 0.0026787454 0.0032670409 2.773835e-03
## Polymyxa 0.0008036236 0.0005392204 8.647837e-04
## Apodus 0.0027518021 0.0004916421 8.974171e-04
## Arthopyrenia 0.0013637249 0.0027753989 9.790004e-04
## Zasmidium 0.0018020651 0.0007771117 5.874003e-04
## X.uncultured.Agaricales. 0.0020699396 0.0008722682 1.256384e-03
## X.uncultured.Glomerales. 0.0006331580 0.0008881276 1.794834e-03
## Ochroconis 0.0007792714 0.0017286770 1.289017e-03
## X.uncultured.Basidiomycota. 0.0007305669 0.0019824278 1.958001e-04
## Microdochium 0.0006331580 0.0004440638 1.142167e-04
## X.uncultured.Hypocreales. 0.0014124294 0.0019031306 7.342503e-04
## X.uncultured.Mortierellales. 0.0007305669 0.0007136740 2.284334e-04
## X.uncultured.Ascomycota. 0.0016315995 0.0009832842 8.158337e-04
## Allovahlkampfia 0.0004870446 0.0002378913 1.142167e-04
## Rhodotorula 0.0056740697 0.0018872712 7.424087e-03
## Dioszegia 0.0025326320 0.0004123450 6.738786e-03
## Alpinaria 0.0001704656 0.0107368287 9.790004e-04
## Leucosporidium 0.0024352231 0.0005709392 1.240067e-03
## Trematosphaeria 0.0009984415 0.0030132902 7.342503e-04
## Paraphoma 0.0026787454 0.0026009452 7.668837e-04
## Neoascochyta 0.0010471459 0.0003806261 1.533767e-03
## Barnettozyma 0.0015585428 0.0054239224 1.223751e-03
## Apiotrichum 0.0001065190 0.0083896343 2.268018e-03
## Waitea 0.0014367816 0.0002854696 8.321504e-04
## Dendryphion 0.0010471459 0.0025850858 2.170118e-03
## Hyaloscypha 0.0001491265 0.0019189901 2.300651e-03
## Neopyrenochaeta 0.0017046561 0.0013163320 9.463671e-04
## Cladophialophora 0.0017533606 0.0025057887 1.256384e-03
## Nullicamyces 0.0010227937 0.0017921147 4.242335e-04
## Rhizophagus 0.0015585428 0.0023947727 1.468501e-04
## Spizellomyces 0.0002922268 0.0020141466 6.526670e-04
## Neohendersonia 0.0007062147 0.0001810822 3.916002e-04
## Oidiodendron 0.0015098383 0.0009674247 5.221336e-04
## Fusidium 0.0003652835 0.0004599232 5.058169e-04
## Leptosphaeria 0.0171683226 0.0012846132 7.016170e-04
## X.uncultured.eukaryote. 0.0004626924 0.0006819551 9.790004e-05
## Stemphylium 0.0014367816 0.0001427348 1.142167e-03
## Trichoderma 0.0001550084 0.0008564088 3.100168e-04
## Fimicolochytrium 0.0005357491 0.0005233609 7.668837e-04
## Volutella 0.0003165790 0.0003330479 1.305334e-04
## X.uncultured.Monoblepharidales. 0.0004139879 0.0007136740 6.689836e-04
## Chlamydomonas 0.0003652835 0.0001744536 1.305334e-04
## Peziza 0.0002435223 0.0001585942 1.468501e-04
## Delitschia 0.0004139879 0.0013004726 2.773835e-04
## Cyberlindnera 0.0005357491 0.0003489073 2.681109e-05
## Chrysosporium 0.0043834015 0.0011577378 2.300651e-03
## Neohelicomyces 0.0005601013 0.0011735972 3.100168e-04
## X.uncultured.Ichthyophonida. 0.0018507695 0.0011577378 6.391138e-05
## Coprinus 0.0001704303 0.0012528943 2.268018e-03
## 16 17 18
## Candida 8.335901e-02 5.146564e-02 4.669838e-02
## Mrakia 1.089542e-01 4.171709e-02 7.119479e-02
## Colletotrichum 4.128921e-03 9.748555e-03 7.321929e-03
## Cladosporium 5.850332e-02 7.032406e-02 2.760063e-02
## Sporobolomyces 3.580452e-02 1.737932e-02 3.566488e-02
## Juxtiphoma 3.412009e-02 5.328089e-02 4.221075e-02
## Sistotrema 3.204536e-02 5.580207e-02 9.501636e-02
## Gibellulopsis 1.345494e-02 2.033750e-02 1.815298e-02
## Botrytis 8.648138e-03 8.370311e-03 3.360664e-02
## Podospora 5.443602e-03 6.171843e-02 8.401660e-03
## Alternaria 1.670056e-02 2.477477e-02 1.568985e-02
## Fusarium 1.314681e-02 1.593384e-02 1.245065e-02
## Mortierella 7.230747e-02 8.340056e-02 1.143840e-01
## Cadophora 9.777942e-03 1.085787e-02 1.531869e-02
## Aspergillus 1.774820e-02 2.659002e-02 2.982758e-02
## Laetinaevia 1.170888e-02 8.807315e-03 3.880285e-03
## Paraphaeosphaeria 9.551981e-03 1.079064e-02 1.717448e-02
## Tetracladium 7.148580e-03 5.781901e-03 8.570368e-03
## Solicoccozyma 2.087057e-02 1.855587e-02 2.439518e-02
## Chloridium 1.053799e-02 3.781767e-02 2.334919e-02
## Trichosporiella 8.833015e-03 6.756757e-03 1.147215e-02
## Vishniacozyma 7.805920e-02 1.321097e-02 5.668590e-03
## Umbelopsis 2.801915e-02 2.131236e-02 4.281810e-02
## Plectosphaerella 6.717200e-03 4.097754e-02 3.003003e-03
## Tausonia 1.123642e-02 3.664112e-03 4.116476e-03
## Chordomyces 3.574290e-03 6.386984e-03 1.180956e-03
## Minimedusa 7.538876e-03 1.290843e-02 1.032493e-02
## Urceolella 1.372199e-02 1.015194e-02 1.393528e-02
## Naganishia 1.454366e-02 3.832190e-03 3.914026e-03
## Acremonium 7.600501e-03 1.179911e-02 1.703951e-02
## X.uncultured.fungus. 1.337277e-02 2.524539e-02 1.724196e-02
## Talaromyces 2.711530e-03 9.244319e-03 1.687080e-02
## Holtermanniella 5.053306e-03 1.949711e-03 5.668590e-03
## Sporidesmium 3.676999e-03 6.084443e-03 5.061241e-03
## Protoventuria 1.047637e-03 7.429071e-03 1.923272e-03
## Trichocladium 2.916949e-03 2.487562e-03 6.613355e-03
## Gorgomyces 1.848771e-04 4.033885e-04 1.687080e-03
## Papiliotrema 9.572523e-03 3.193492e-03 2.901778e-03
## Ophiosphaerella 1.314681e-03 2.756488e-03 3.542869e-03
## Pseudeurotium 1.643352e-03 5.849133e-03 6.680838e-03
## Coniochaeta 2.629363e-03 4.370042e-03 2.260688e-03
## Exophiala 3.409955e-03 9.378782e-03 1.211324e-02
## NA. 4.888971e-03 7.529918e-03 1.248439e-02
## Sakaguchia 3.081284e-04 5.042356e-04 2.091980e-03
## Pseudoanguillospora 3.697541e-04 2.050558e-03 8.772818e-04
## Halenospora 1.437933e-03 1.579938e-03 1.315923e-03
## Pleotrichocladium 5.135474e-04 2.016942e-04 1.484631e-03
## Cephalosporium 1.088720e-03 1.042087e-03 7.423153e-04
## X.uncultured.Spizellomycetales. 5.751731e-04 9.076240e-04 2.294429e-03
## Verticillium 2.547195e-03 3.563265e-03 1.180956e-03
## Pseudogymnoascus 5.751731e-04 3.865806e-03 9.447650e-04
## Devriesia 1.396849e-03 2.554794e-03 2.665587e-03
## Polymyxa 2.465027e-04 4.370042e-04 6.748321e-04
## Apodus 1.479016e-03 2.823719e-03 1.147215e-03
## Arthopyrenia 1.766603e-03 2.050558e-03 2.631845e-03
## Zasmidium 1.684435e-03 1.613554e-03 2.294429e-03
## X.uncultured.Agaricales. 4.108379e-05 7.059298e-04 6.748321e-04
## X.uncultured.Glomerales. 5.546312e-04 2.084174e-03 1.653339e-03
## Ochroconis 5.135474e-04 6.386984e-04 1.687080e-03
## X.uncultured.Basidiomycota. 1.540642e-03 2.722872e-03 2.699329e-04
## Microdochium 1.437933e-04 1.008471e-04 1.079731e-03
## X.uncultured.Hypocreales. 2.403402e-03 2.487562e-03 1.788305e-03
## X.uncultured.Mortierellales. 7.805920e-04 1.042087e-03 1.214698e-03
## X.uncultured.Ascomycota. 1.437933e-04 2.050558e-03 1.889530e-03
## Allovahlkampfia 7.395082e-04 5.714670e-04 8.097986e-04
## Rhodotorula 1.994618e-02 5.916364e-03 9.447650e-04
## Dioszegia 1.066124e-02 1.479091e-03 7.423153e-04
## Alpinaria 1.700869e-02 1.848864e-03 8.361004e-05
## Leucosporidium 2.384914e-02 1.210165e-03 4.386409e-04
## Trematosphaeria 3.286703e-04 8.740083e-04 1.147215e-03
## Paraphoma 8.627596e-04 4.706199e-04 3.104228e-03
## Neoascochyta 3.594832e-03 5.378513e-04 1.903131e-04
## Barnettozyma 7.805920e-03 2.991798e-03 7.524378e-03
## Apiotrichum 2.403402e-03 1.210165e-03 2.665587e-03
## Waitea 4.313798e-04 3.596880e-03 3.070486e-03
## Dendryphion 3.081284e-04 1.411860e-03 3.374161e-04
## Hyaloscypha 2.937491e-03 1.815248e-03 1.045990e-03
## Neopyrenochaeta 8.216758e-04 1.109318e-03 1.079731e-03
## Cladophialophora 2.670446e-03 1.613554e-03 1.788305e-03
## Nullicamyces 8.833015e-04 2.353099e-03 2.395654e-03
## Rhizophagus 5.751731e-04 2.353099e-03 1.822047e-03
## Spizellomyces 7.189663e-04 4.033885e-04 9.785066e-04
## Neohendersonia 9.038434e-04 1.075703e-03 9.110234e-04
## Oidiodendron 7.395082e-04 1.479091e-03 4.386409e-04
## Fusidium 8.216758e-04 4.370042e-04 5.736073e-04
## Leptosphaeria 7.600501e-04 8.282682e-05 8.282682e-05
## X.uncultured.eukaryote. 2.130379e-05 1.344628e-04 2.024496e-04
## Stemphylium 1.643352e-03 6.723141e-04 5.398657e-04
## Trichoderma 2.690988e-03 3.361571e-03 2.024496e-03
## Fimicolochytrium 2.403402e-03 2.616805e-04 1.045990e-03
## Volutella 6.778825e-04 3.917697e-05 3.036745e-04
## X.uncultured.Monoblepharidales. 7.805920e-04 9.748555e-04 8.772818e-04
## Chlamydomonas 8.216758e-05 3.185647e-05 5.061241e-04
## Peziza 3.492122e-04 6.723141e-05 2.024496e-04
## Delitschia 1.848771e-04 8.740083e-04 3.745318e-03
## Cyberlindnera 6.367988e-04 7.059298e-04 2.681109e-05
## Chrysosporium 7.292373e-03 1.469006e-02 9.447650e-03
## Neohelicomyces 3.180864e-05 4.941509e-03 3.272936e-03
## X.uncultured.Ichthyophonida. 1.417391e-03 5.714670e-04 2.361912e-03
## Coprinus 1.704303e-04 4.706199e-04 2.260688e-03
##
## $meta.dat.use
## ndvi_01
## 1 0.6887884
## 2 0.8302155
## 3 -1.9625407
## 4 -0.7571646
## 5 0.9980715
## 6 0.5095020
## 7 -1.9896865
## 8 -1.1410253
## 9 0.5747102
## 10 -1.0529250
## 11 0.9838132
## 12 0.6228720
## 13 0.6121273
## 14 -0.8421145
## 15 0.3130208
## 16 0.5945529
## 17 0.6619353
## 18 0.3558477
##
## $wald
## $wald$beta
## Candida Mrakia Colletotrichum Cladosporium Sporobolomyces
## (Intercept) 4.3943512 5.480705 1.6935183 3.7208385 2.361759
## ndvi_01 0.1633888 -0.186189 -0.6151762 0.8981771 1.555382
## Juxtiphoma Sistotrema Gibellulopsis Botrytis Podospora Alternaria
## (Intercept) 4.2962572 4.00035068 3.36813923 2.4976342 1.573231 3.2919764
## ndvi_01 -0.0631729 -0.03522596 -0.03586229 0.6043581 -0.351179 -0.1794338
## Fusarium Mortierella Cadophora Aspergillus Laetinaevia
## (Intercept) 3.0308770 4.97791414 2.8276407 2.9561805 1.8360267
## ndvi_01 -0.4266206 0.01413217 -0.3844973 0.1520078 -0.2894733
## Paraphaeosphaeria Tetracladium Solicoccozyma Chloridium
## (Intercept) 2.5064018 2.6740797 3.20726703 3.2647339
## ndvi_01 -0.1794086 -0.5333643 -0.04885714 -0.3753921
## Trichosporiella Vishniacozyma Umbelopsis Plectosphaerella
## (Intercept) 2.6664050 2.3957689 2.9736169 0.4749363
## ndvi_01 -0.7826106 0.8232492 0.2148238 0.5825941
## Tausonia Chordomyces Minimedusa Urceolella Naganishia Acremonium
## (Intercept) 1.9979638 -0.5922402 1.7529473 2.2111112 1.0852263 1.2086428
## ndvi_01 -0.1658491 0.9771266 0.3072024 -0.3440139 0.3405805 0.2466034
## X.uncultured.fungus. Talaromyces Holtermanniella Sporidesmium
## (Intercept) 2.36708491 0.3413776 0.6607865 0.7777615
## ndvi_01 0.07150662 0.1472212 0.1290130 -0.2336057
## Protoventuria Trichocladium Gorgomyces Papiliotrema Ophiosphaerella
## (Intercept) -0.1039228 0.7004752 -1.635784 0.75577912 0.1535562
## ndvi_01 -0.1026144 -0.2233561 -1.042979 -0.02668366 -0.1293585
## Pseudeurotium Coniochaeta Exophiala NA. Sakaguchia
## (Intercept) -0.5874280 0.008542792 1.3376854 1.2430630 -1.3949950
## ndvi_01 0.2886117 -0.387755956 -0.2492913 0.1104767 -0.3897049
## Pseudoanguillospora Halenospora Pleotrichocladium Cephalosporium
## (Intercept) -1.6682014 -0.4958424 -0.5823653 -0.5442522
## ndvi_01 -0.1165233 -0.4015825 -0.4839507 -0.2181864
## X.uncultured.Spizellomycetales. Verticillium Pseudogymnoascus
## (Intercept) -0.7362870 -0.3726311 -1.562428
## ndvi_01 -0.1799865 0.3314485 0.079174
## Devriesia Polymyxa Apodus Arthopyrenia Zasmidium
## (Intercept) -0.22071715 -1.7540812 -1.3755398 -0.854181939 -1.4551112
## ndvi_01 0.01235102 -0.5495672 0.3621303 0.005794465 0.2909076
## X.uncultured.Agaricales. X.uncultured.Glomerales. Ochroconis
## (Intercept) -1.61593844 -1.4549153 -1.5905404
## ndvi_01 0.09156544 0.0183262 -0.1570773
## X.uncultured.Basidiomycota. Microdochium X.uncultured.Hypocreales.
## (Intercept) -1.5365999 -2.47867380 -1.099977
## ndvi_01 -0.1464914 -0.01716159 -0.183888
## X.uncultured.Mortierellales. X.uncultured.Ascomycota.
## (Intercept) -2.3518590 -1.5697845
## ndvi_01 0.2827829 0.1534251
## Allovahlkampfia Rhodotorula Dioszegia Alpinaria Leucosporidium
## (Intercept) -2.3991455 0.4055591 -0.5740281 -0.6585266 -1.1389698
## ndvi_01 -0.1521923 0.9698252 1.0017473 0.1105339 0.7644526
## Trematosphaeria Paraphoma Neoascochyta Barnettozyma Apiotrichum
## (Intercept) -1.0185630 -0.5589414 -0.85186696 -0.3268341 -0.698244019
## ndvi_01 -0.9936727 -0.5990378 0.01292847 0.4839991 -0.009980609
## Waitea Dendryphion Hyaloscypha Neopyrenochaeta Cladophialophora
## (Intercept) -1.4992086 -1.1388736 -0.9967909 -1.6593325 -0.7678721
## ndvi_01 0.2196045 -0.6167296 -0.5865611 -0.6042038 -0.4611709
## Nullicamyces Rhizophagus Spizellomyces Neohendersonia Oidiodendron
## (Intercept) -1.437574 -2.0622345 -1.6154938 -1.7041040 -2.1240550
## ndvi_01 0.351313 0.7150012 -0.3090265 0.1651187 -0.1016075
## Fusidium Leptosphaeria X.uncultured.eukaryote. Stemphylium
## (Intercept) -2.8111793 -1.3427979 -3.114200 -2.0757193
## ndvi_01 0.2511801 -0.9716771 -1.287955 0.7787973
## Trichoderma Fimicolochytrium Volutella
## (Intercept) -1.56638930 -1.6226395 -3.277302
## ndvi_01 -0.05379201 -0.1719723 0.835822
## X.uncultured.Monoblepharidales. Chlamydomonas Peziza Delitschia
## (Intercept) -2.0081261 -3.6176448 -4.0562009 -2.244267
## ndvi_01 0.5717855 0.1391061 0.8324001 1.010332
## Cyberlindnera Chrysosporium Neohelicomyces
## (Intercept) -2.8909671 -0.2124255 -2.6419124
## ndvi_01 0.4509643 0.3419751 -0.3570097
## X.uncultured.Ichthyophonida. Coprinus
## (Intercept) -1.8464698 -1.284977
## ndvi_01 -0.7154673 -1.033100
##
## $wald$sig
## Candida Mrakia
## 1.2215077 0.5700074
## Colletotrichum Cladosporium
## 1.4036692 0.9963434
## Sporobolomyces Juxtiphoma
## 1.2951373 0.5702959
## Sistotrema Gibellulopsis
## 1.0382575 0.6504606
## Botrytis Podospora
## 1.2424607 0.9818834
## Alternaria Fusarium
## 0.7672150 0.8955881
## Mortierella Cadophora
## 0.4146667 0.4010600
## Aspergillus Laetinaevia
## 0.2560520 0.9197351
## Paraphaeosphaeria Tetracladium
## 0.5929737 0.8545731
## Solicoccozyma Chloridium
## 0.4280061 0.5158491
## Trichosporiella Vishniacozyma
## 0.7508610 1.1626840
## Umbelopsis Plectosphaerella
## 0.7275887 1.1651668
## Tausonia Chordomyces
## 0.8205193 1.1955553
## Minimedusa Urceolella
## 0.7042566 0.4253511
## Naganishia Acremonium
## 0.7021013 0.7947845
## X.uncultured.fungus. Talaromyces
## 0.4515477 1.3280874
## Holtermanniella Sporidesmium
## 0.7476119 0.5905748
## Protoventuria Trichocladium
## 0.6732226 0.5222306
## Gorgomyces Papiliotrema
## 1.2212104 0.6753352
## Ophiosphaerella Pseudeurotium
## 0.4781341 1.3161740
## Coniochaeta Exophiala
## 0.6135353 0.6047666
## NA. Sakaguchia
## 0.5156342 0.8787618
## Pseudoanguillospora Halenospora
## 1.2508948 0.6758848
## Pleotrichocladium Cephalosporium
## 1.1606239 0.7193976
## X.uncultured.Spizellomycetales. Verticillium
## 1.3556481 0.7873128
## Pseudogymnoascus Devriesia
## 0.8000965 0.5005736
## Polymyxa Apodus
## 0.7114220 1.0420095
## Arthopyrenia Zasmidium
## 0.5995660 0.6262052
## X.uncultured.Agaricales. X.uncultured.Glomerales.
## 1.6566737 0.8338330
## Ochroconis X.uncultured.Basidiomycota.
## 0.7595471 0.9586198
## Microdochium X.uncultured.Hypocreales.
## 1.2072850 0.8541804
## X.uncultured.Mortierellales. X.uncultured.Ascomycota.
## 1.2812051 1.0325138
## Allovahlkampfia Rhodotorula
## 1.0394656 1.6957272
## Dioszegia Alpinaria
## 2.0597151 2.4761473
## Leucosporidium Trematosphaeria
## 1.4913813 1.2387254
## Paraphoma Neoascochyta
## 2.0395700 1.7246924
## Barnettozyma Apiotrichum
## 1.7714708 1.8265809
## Waitea Dendryphion
## 1.6527961 1.0477282
## Hyaloscypha Neopyrenochaeta
## 1.1779257 1.0922914
## Cladophialophora Nullicamyces
## 0.7526203 0.8996428
## Rhizophagus Spizellomyces
## 1.7075232 1.0428119
## Neohendersonia Oidiodendron
## 0.7569146 1.3567426
## Fusidium Leptosphaeria
## 0.7891193 1.8397478
## X.uncultured.eukaryote. Stemphylium
## 1.5222312 1.7198369
## Trichoderma Fimicolochytrium
## 1.2452739 0.8155576
## Volutella X.uncultured.Monoblepharidales.
## 1.3525686 0.8089034
## Chlamydomonas Peziza
## 1.4681510 0.7190064
## Delitschia Cyberlindnera
## 3.1648003 2.3812635
## Chrysosporium Neohelicomyces
## 1.8742136 2.1214184
## X.uncultured.Ichthyophonida. Coprinus
## 1.9712618 1.2302890
##
## $wald$X
## (Intercept) ndvi_01
## 1 1 0.6887884
## 2 1 0.8302155
## 3 1 -1.9625407
## 4 1 -0.7571646
## 5 1 0.9980715
## 6 1 0.5095020
## 7 1 -1.9896865
## 8 1 -1.1410253
## 9 1 0.5747102
## 10 1 -1.0529250
## 11 1 0.9838132
## 12 1 0.6228720
## 13 1 0.6121273
## 14 1 -0.8421145
## 15 1 0.3130208
## 16 1 0.5945529
## 17 1 0.6619353
## 18 1 0.3558477
## attr(,"assign")
## [1] 0 1
##
## $wald$bias
## [1] -1.26042852 -0.06003912
# Show effect size and significance plots
linda.plot(
l_model,
variables.plot = c('ndvi_01'),
alpha = 0.05,
lfc.cut = 1,
legend = TRUE
)
## $plot.lfc
## $plot.lfc[[1]]
##
##
## $plot.volcano
## $plot.volcano[[1]]
l_model_df <- as.data.frame(l_model$output)
write.xlsx(l_model_df, file = "supplementary_table_ndvi_regression_fits2.xlsx", rowNames = TRUE, colnames = TRUE)
This script is based on ideas and code from the dada2 Tutorial by Benjamin Callahan, the publication “Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses” by Callahan et al. (2016) and various pages of the official phyloseq website by Paul J. McMurdie.
sessionInfo()
## R version 4.4.2 (2024-10-31)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.5 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
##
## locale:
## [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
## [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
## [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
## [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
##
## time zone: Europe/Oslo
## tzcode source: system (glibc)
##
## attached base packages:
## [1] parallel stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] effectsize_1.0.0 MicrobiomeStat_1.2 aod_1.3.3
## [4] BBmisc_1.13 betareg_3.2-1 ggpmisc_0.6.1
## [7] ggpp_0.5.8-1 openxlsx_4.2.7.1 readxl_1.4.3
## [10] lubridate_1.9.4 forcats_1.0.0 stringr_1.5.1
## [13] dplyr_1.1.4 purrr_1.0.2 readr_2.1.5
## [16] tidyr_1.3.1 tibble_3.2.1 tidyverse_2.0.0
## [19] ggpubr_0.6.0 viridis_0.6.5 viridisLite_0.4.2
## [22] phangorn_2.12.1 biomformat_1.34.0 vegan_2.6-8
## [25] lattice_0.22-6 permute_0.9-7 scales_1.3.0
## [28] gridExtra_2.3 ape_5.8-1 reshape2_1.4.4
## [31] phyloseq_1.50.0 ggplot2_3.5.1 cuphyr_0.3
## [34] DECIPHER_3.2.0 Biostrings_2.74.0 GenomeInfoDb_1.42.1
## [37] XVector_0.46.0 IRanges_2.40.0 S4Vectors_0.44.0
## [40] BiocGenerics_0.52.0 dada2_1.34.0 Rcpp_1.0.13-1
##
## loaded via a namespace (and not attached):
## [1] fs_1.6.5 matrixStats_1.4.1
## [3] bitops_1.0-9 devtools_2.4.5
## [5] httr_1.4.7 RColorBrewer_1.1-3
## [7] insight_1.0.0 numDeriv_2016.8-1.1
## [9] profvis_0.4.0 tools_4.4.2
## [11] backports_1.5.0 utf8_1.2.4
## [13] R6_2.5.1 mgcv_1.9-1
## [15] rhdf5filters_1.18.0 urlchecker_1.0.1
## [17] withr_3.0.2 textshaping_0.4.1
## [19] quantreg_5.99.1 cli_3.6.3
## [21] Biobase_2.66.0 formatR_1.14
## [23] sandwich_3.1-1 labeling_0.4.3
## [25] sass_0.4.9 systemfonts_1.1.0
## [27] Rsamtools_2.22.0 sessioninfo_1.2.2
## [29] rstudioapi_0.17.1 generics_0.1.3
## [31] hwriter_1.3.2.1 car_3.1-3
## [33] zip_2.3.1 Matrix_1.7-1
## [35] interp_1.1-6 abind_1.4-8
## [37] lifecycle_1.0.4 yaml_2.3.10
## [39] carData_3.0-5 SummarizedExperiment_1.36.0
## [41] rhdf5_2.50.0 SparseArray_1.6.0
## [43] grid_4.4.2 promises_1.3.2
## [45] crayon_1.5.3 pwalign_1.2.0
## [47] miniUI_0.1.1.1 cowplot_1.1.3
## [49] pillar_1.10.0 knitr_1.49
## [51] GenomicRanges_1.58.0 statip_0.2.3
## [53] boot_1.3-31 codetools_0.2-20
## [55] fastmatch_1.1-4 glue_1.8.0
## [57] ShortRead_1.64.0 data.table_1.16.4
## [59] remotes_2.5.0 vctrs_0.6.5
## [61] png_0.1-8 cellranger_1.1.0
## [63] gtable_0.3.6 datawizard_0.13.0
## [65] cachem_1.1.0 xfun_0.49
## [67] S4Arrays_1.6.0 mime_0.12
## [69] modeest_2.4.0 survival_3.8-3
## [71] timeDate_4041.110 iterators_1.0.14
## [73] statmod_1.5.0 ellipsis_0.3.2
## [75] nlme_3.1-166 usethis_3.1.0
## [77] fBasics_4041.97 bslib_0.8.0
## [79] rpart_4.1.23 colorspace_2.1-1
## [81] DBI_1.2.3 nnet_7.3-19
## [83] ade4_1.7-22 tidyselect_1.2.1
## [85] timeSeries_4041.111 compiler_4.4.2
## [87] curl_6.0.1 SparseM_1.84-2
## [89] DelayedArray_0.32.0 bayestestR_0.15.0
## [91] checkmate_2.3.2 lmtest_0.9-40
## [93] quadprog_1.5-8 spatial_7.3-17
## [95] digest_0.6.37 minqa_1.2.8
## [97] rmarkdown_2.29 htmltools_0.5.8.1
## [99] pkgconfig_2.0.3 jpeg_0.1-10
## [101] lme4_1.1-35.5 MatrixGenerics_1.18.0
## [103] stabledist_0.7-2 fastmap_1.2.0
## [105] rlang_1.1.4 htmlwidgets_1.6.4
## [107] UCSC.utils_1.2.0 shiny_1.10.0
## [109] farver_2.1.2 jquerylib_0.1.4
## [111] zoo_1.8-12 jsonlite_1.8.9
## [113] BiocParallel_1.40.0 magrittr_2.0.3
## [115] polynom_1.4-1 modeltools_0.2-23
## [117] Formula_1.2-5 GenomeInfoDbData_1.2.13
## [119] parameters_0.24.0 Rhdf5lib_1.28.0
## [121] munsell_0.5.1 stringi_1.8.4
## [123] stable_1.1.6 zlibbioc_1.52.0
## [125] MASS_7.3-61 plyr_1.8.9
## [127] pkgbuild_1.4.5 flexmix_2.3-19
## [129] ggrepel_0.9.6 deldir_2.0-4
## [131] splines_4.4.2 multtest_2.62.0
## [133] hms_1.1.3 igraph_2.1.2
## [135] ggsignif_0.6.4 rmutil_1.1.10
## [137] pkgload_1.4.0 evaluate_1.0.1
## [139] latticeExtra_0.6-30 RcppParallel_5.1.9
## [141] nloptr_2.1.1 tzdb_0.4.0
## [143] foreach_1.5.2 httpuv_1.6.15
## [145] MatrixModels_0.5-3 clue_0.3-66
## [147] broom_1.0.7 xtable_1.8-4
## [149] rstatix_0.7.2 later_1.4.1
## [151] ragg_1.3.3 lmerTest_3.1-3
## [153] memoise_2.0.1 GenomicAlignments_1.42.0
## [155] cluster_2.1.8 timechange_0.3.0