Chapter 8 Microbial Composition
We use stacked barplot to show the differences of microbial composition among samples or groups. You can choose the specific taxonomic level to visualize the whole microbial composition.
Outline of this Chapter:
8.2 Importing Data
data("dada2_ps")
dada2_ps_remove_BRS <- get_GroupPhyloseq(
ps = dada2_ps,
group = "Group",
group_names = "QC",
discard = TRUE)
dada2_ps_rarefy <- norm_rarefy(object = dada2_ps_remove_BRS,
size = 51181)
dada2_ps_rarefy## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 891 taxa and 23 samples ]
## sample_data() Sample Data: [ 23 samples by 1 sample variables ]
## tax_table() Taxonomy Table: [ 891 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 891 tips and 888 internal nodes ]
## refseq() DNAStringSet: [ 891 reference sequences ]MGS dataset
data("metaphlan2_ps")
metaphlan2_ps_remove_BRS <- get_GroupPhyloseq(
ps = metaphlan2_ps,
group = "Group",
group_names = "QC",
discard = TRUE)
metaphlan2_ps_remove_BRS## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 326 taxa and 22 samples ]
## sample_data() Sample Data: [ 22 samples by 2 sample variables ]
## tax_table() Taxonomy Table: [ 326 taxa by 7 taxonomic ranks ]
8.4 plot_StackBarPlot from XAMS2
plot_StackBarPlot provides too many parameters for users to display the Stacked barplot of microbial composition by using ggplot2 format. Here is the ordinary pattern. More details to see help(plot_StackBarPlot).
Figure 8.2: Stacked barplot Ordinary pattern
Please open the below buttons, if you want to see other options for stacked barplot.
genus level in stacked barplot
dada2_ps_rarefy_genus <- summarize_taxa(ps = dada2_ps_rarefy,
taxa_level = "Genus")
otu_tab <- phyloseq::otu_table(dada2_ps_rarefy_genus)
sam_tab <- phyloseq::sample_data(dada2_ps_rarefy_genus)
plot_StackBarPlot(
data_otu = otu_tab,
data_sam = sam_tab,
cutoff = 0.01,
taxa_level = "Genus")
Figure 8.3: Stacked barplot otu_tab and sample_table as input
Metadata with Group phenotype
## [1] "This palatte have 20 colors!"
Figure 8.4: Stacked barplot Metadata with group
Metadata with Group phenotype in cluster mode
## [1] "This palatte have 20 colors!"
Figure 8.5: Stacked barplot Metadata with group in cluster mode
Metadata with Group phenotype in facet
Figure 8.6: Stacked barplot Metadata with group in facet
hiding sample_label
plot_StackBarPlot(
ps = dada2_ps_rarefy,
taxa_level = "Phylum",
group = "Group",
facet = TRUE,
sample_label = FALSE)
Figure 8.7: Stacked barplot by hiding samples’ names
- two annotations for column
## [1] "This palatte have 19 colors!"
## [1] "This palatte have 20 colors!"
## [1] "This palatte have 20 colors!"
## [1] "This palatte have 20 colors!"
Figure 8.8: Stacked barplot Metadata with two annotation
- three annotations for column
plot_StackBarPlot(
ps = amplicon_ps,
taxa_level = "Order",
group = "SampleType",
subgroup = c("Year", "Month"))## [1] "This palatte have 19 colors!"
## [1] "This palatte have 20 colors!"
## [1] "This palatte have 20 colors!"
## [1] "This palatte have 20 colors!"
## [1] "This palatte have 20 colors!"
## [1] "This palatte have 20 colors!"
Figure 8.9: Stacked barplot Metadata with three annotation
- OrderSampleID
plot_StackBarPlot(
ps = amplicon_ps,
taxa_level = "Order",
group = "SampleType",
orderSample = phyloseq::sample_names(amplicon_ps)[1:10])## [1] "This palatte have 20 colors!"
Figure 8.10: Stacked barplot Metadata with OrderSampleID
8.5 Heatmaps
plot_taxa_heatmap(ps = dada2_ps_rarefy,
taxa_level = "Phylum",
cutoff = 1e-4,
colors = c("black", "yellow"))
Figure 8.11: Heatmaps
8.6 Systematic Information
## ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
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## date 2023-11-30
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