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3.3_explorative_analysis_ampvis2.R
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# ######################################################################
#
## Explorative analysis: Ordination figures (CCA)
#
# ######################################################################
# ##############################################################################
# Set-up
setwd("~/Desktop/crc_analysis/scripts") #macbook
setwd("C:/Users/Erika Dvarionaite/iCloudDrive/Desktop/crc_analysis/scripts") #windows
library(readr)
library(dplyr)
library(ampvis2)
library(ggplot2)
library(stringr)
library(tibble)
library(patchwork)
memory.limit(56000)
memory.size(T)
# ##############################################################################
# Get data
kegg_relab <- read.table("../data/kegg/filtered_kegg_full.tsv", sep = "\t", stringsAsFactors = F, header = T, check.names = F, row.names = 1, quote ="", fill = F)
go_relab <- read.table("../data/go/filtered_go_full.tsv", sep = "\t", stringsAsFactors = F, header = T, check.names = F, row.names = 1, quote ="", fill = F)
eggnog_relab <- read.table("../data/eggnog/filtered_eggnog_full.tsv", sep = "\t", stringsAsFactors = F, header = T, check.names = F, row.names = 1, quote ="", fill = F)
pfam_relab <- read.table("../data/pfam/filtered_pfam_full.tsv", sep = "\t", stringsAsFactors = F, header = T, check.names = F, row.names = 1, quote ="", fill = F)
level4ec_relab <- read.table("../data/level4ec/filtered_level4ec_full.tsv", sep = "\t", stringsAsFactors = F, header = T, check.names = F, row.names = 1, quote ="", fill = F)
species_relab <- read.table('../data/species/filtered.species.tsv', sep = "\t", stringsAsFactors = F, header = T, check.names = F, row.names = 1, quote ="", fill = F)
meta.all <- read_tsv(file = '../data/meta/meta.crc.tsv')
# ##############################################################################
# Table preparation & removal of outliers
ampvis_kegg <- kegg_relab %>% rownames_to_column(var="OTU") %>% subset(select=-SAMD00164778)
ampvis_eggnog <- eggnog_relab %>% rownames_to_column(var="OTU") %>% subset(select=-SAMD00164778) %>% subset(select=-HP)
ampvis_pfam <- pfam_relab %>% rownames_to_column(var="OTU") %>% subset(select=-SAMD00164778)
ampvis_go <- go_relab %>% rownames_to_column(var="OTU") %>% subset(select=-SAMD00164778)
ampvis_level4ec <- level4ec_relab %>% rownames_to_column(var="OTU") %>% subset(select=-SAMD00164778)
ampvis_species <- species_relab %>% rownames_to_column(var="OTU") %>% subset(select=-SAMD00164778)
# ##############################################################################
# Creating an ampvis2 object
kegg <- amp_load(otutable = ampvis_kegg,
metadata = meta.all)
eggnog <- amp_load(otutable = ampvis_eggnog,
metadata = meta.all)
go <- amp_load(otutable = ampvis_go,
metadata = meta.all)
level4ec <- amp_load(otutable = ampvis_level4ec,
metadata = meta.all)
pfam <- amp_load(otutable = ampvis_pfam,
metadata = meta.all)
species <- amp_load(otutable = ampvis_species,
metadata = meta.all)
# ##############################################################################
# General ordination constrained by group (can be changed to by study)
species.cca <- amp_ordinate(species,
type = "CCA",
distmeasure = "none",
constrain = "Group",
sample_color_by = "Group",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p1 = species.cca + labs(title="MetaPhlAn") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p1
ggsave("../figures/ordination/cca/group/species.cca.pdf", last_plot())
ggsave("../figures/ordination/cca/group/species.cca.png", last_plot())
# kegg
kegg.cca <- amp_ordinate(kegg,
type = "CCA",
distmeasure = "none",
constrain = "Group",
sample_color_by = "Group",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p2 = kegg.cca + labs(title="KEGG") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p2
ggsave("../figures/ordination/cca/group/kegg.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/group/kegg.cca.png", plot = last_plot())
# eggnog
eggnog.cca <- amp_ordinate(eggnog,
type = "CCA",
distmeasure = "none",
constrain = "Group",
sample_color_by = "Group",
transform = "log",
filter_species = 0.001,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p3 = eggnog.cca + labs(title="eggNOG") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p3
ggsave("../figures/ordination/cca/group/eggnog.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/group/eggnog.cca.png", plot = last_plot())
# pfam
pfam.cca <- amp_ordinate(pfam,
type = "CCA",
distmeasure = "none",
constrain = "Group",
sample_color_by = "Group",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p4 = pfam.cca + labs(title="Pfam") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p4
ggsave("../figures/ordination/cca/group/pfam.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/group/pfam.cca.png", plot = last_plot())
# go
go.cca <- amp_ordinate(go,
type = "CCA",
distmeasure = "none",
constrain = "Group",
sample_color_by = "Group",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p5 = go.cca + labs(title="GO") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p5
ggsave("../figures/ordination/cca/group/go.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/group/go.cca.png", plot = last_plot())
# enzymes
enzymes.cca <- amp_ordinate(level4ec,
type = "CCA",
distmeasure = "none",
constrain = "Group",
sample_color_by = "Group",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU",
print_caption = T)
p6 = enzymes.cca + labs(title="Enzymes") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p6
ggsave("../figures/ordination/cca/group/enzymes.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/group/enzymes.cca.png", plot = last_plot())
p <- (p1+p2)/(p3+p4)/(p5+p6) + plot_layout(guides="collect")
p
ggsave("../figures/ordination/cca/group/all.cca.pdf", plot = last_plot(), height = 14, width = 10)
ggsave("../figures/ordination/cca/group/all.cca.png", plot = last_plot(), height = 14, width = 10)
# ##############################################################################
# General ordination by group (all studies combined)
species.cca <- amp_ordinate(species,
type = "CCA",
distmeasure = "none",
constrain = "Study",
sample_color_by = "Study",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p1 = species.cca + labs(title="MetaPhlAn") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p1
ggsave("../figures/ordination/cca/species.cca.pdf", last_plot())
ggsave("../figures/ordination/cca/species.cca.png", last_plot())
# kegg
kegg.cca <- amp_ordinate(kegg,
type = "CCA",
distmeasure = "none",
constrain = "Study",
sample_color_by = "Study",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p2 = kegg.cca + labs(title="KEGG") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p2
ggsave("../figures/ordination/cca/kegg.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/kegg.cca.png", plot = last_plot())
# eggnog
eggnog.cca <- amp_ordinate(eggnog,
type = "CCA",
distmeasure = "none",
constrain = "Study",
sample_color_by = "Study",
transform = "log",
filter_species = 0.001,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p3 = eggnog.cca + labs(title="eggNOG") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p3
ggsave("../figures/ordination/cca/eggnog.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/eggnog.cca.png", plot = last_plot())
# pfam
pfam.cca <- amp_ordinate(pfam,
type = "CCA",
distmeasure = "none",
constrain = "Study",
sample_color_by = "Study",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p4 = pfam.cca + labs(title="Pfam") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p4
ggsave("../figures/ordination/cca/pfam.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/pfam.cca.png", plot = last_plot())
# go
go.cca <- amp_ordinate(go,
type = "CCA",
distmeasure = "none",
constrain = "Study",
sample_color_by = "Study",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU")
p5 = go.cca + labs(title="GO") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p5
ggsave("../figures/ordination/cca/go.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/go.cca.png", plot = last_plot())
# enzymes
enzymes.cca <- amp_ordinate(level4ec,
type = "CCA",
distmeasure = "none",
constrain = "Study",
sample_color_by = "Study",
transform = "log",
filter_species = 0.001,
#species_nlabels = 5,
sample_colorframe = T,
species_label_taxonomy = "OTU",
print_caption = T)
p6 = enzymes.cca + labs(title="Enzymes") + theme(plot.title = element_text(hjust = 0.5, size = 20))
p6
ggsave("../figures/ordination/cca/enzymes.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/cca/enzymes.cca.png", plot = last_plot())
p <- (p1+p2)/(p3+p4)/(p5+p6) + plot_layout(guides="collect")
p
ggsave("../figures/ordination/cca/all.cca.pdf", plot = last_plot(), height = 14, width = 10)
ggsave("../figures/ordination/cca/all.cca.png", plot = last_plot(), height = 14, width = 10)
# ##############################################################################
# CCA of IN & US studies by groups
goin <- amp_subset_samples(go, Study == "IN-CRC")
gous <- amp_subset_samples(go, Study == "US-CRC")
gojp <- amp_subset_samples(go, Study == "JP-CRC")
goit2 <- amp_subset_samples(go, Study == "IT-CRC-2")
gode <- amp_subset_samples(go, Study == "DE-CRC")
gofr <- amp_subset_samples(go, Study == "FR-CRC")
goin.cca <- amp_ordinate(goin,
type = "CCA",
distmeasure = "none",
constrain = "Group",
sample_color_by = "Group",
transform = "log",
filter_species = 0.001,
sample_colorframe = T,
species_label_taxonomy = "OTU")
ind = goin.cca + labs(title="Indian cohort") + theme(plot.title = element_text(size = 20))
ind
ggsave("../figures/ordination/goin.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/goin.cca.png", plot = last_plot())
gous.cca <- amp_ordinate(gous,
type = "CCA",
distmeasure = "none",
constrain = "Group",
sample_color_by = "Group",
transform = "log",
filter_species = 0.001,
sample_colorframe = T,
species_label_taxonomy = "OTU")
us = gous.cca + labs(title="US cohort") + theme(plot.title = element_text(size = 20))
us
ggsave("../figures/ordination/goin.cca.pdf", plot = last_plot())
ggsave("../figures/ordination/goin.cca.png", plot = last_plot())
p <- (ind+us) + plot_layout(guides="collect")
p
ggsave("../figures/ordination/cca/indus.cca.pdf", plot = last_plot(), width = 10)
ggsave("../figures/ordination/cca/indus.cca.png", plot = last_plot(), width = 10)