Chapter 7 Microbial composition
Loading packages
A whole picture of the microbial composition.
7.1 Stacked barplot
- XVIZ package
- XMAS package
plot_StackBarPlot(
ps = metaphlan2_ps_LOD_species,
taxa_level = "Phylum",
group = "Group",
cluster = TRUE)
## [1] "This palatte have 20 colors!"
7.2 Core microbiota
prevalences <- seq(0.05, 1, 0.05)
detections <- 10^seq(log10(1e-3), log10(0.2), length = 10)
pl_core <- plot_core_taxa(metaphlan2_ps_LOD_species,
plot.type = "heatmap",
colours = gray(seq(0, 1, length=5)),
prevalences = prevalences,
detections = detections,
min.prevalence = 0.5)+
xlab("Detection Threshold (Relative Abundance (%))")
pl_core
The degree of color indicates the size of abundance and prevalence.
- Use
core_members
to obtain the core taxa. detection for abundance and prevalence for occurrence.
core_taxa_name <- core_members(metaphlan2_ps_LOD_species,
detection = 0.01,
prevalence = 0.5)
print(core_taxa_name)
## [1] "s__Bacteroides_uniformis" "s__Bacteroides_vulgatus" "s__Faecalibacterium_prausnitzii" "s__Ruminococcus_sp_5_1_39BFAA"
Result:
Only 4 genera (s__Bacteroides_uniformis, s__Bacteroides_vulgatus, s__Faecalibacterium_prausnitzii and s__Ruminococcus_sp_5_1_39BFAA) passed the threshold of detection and prevalence which we choose.
7.3 Systematic Information
## ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## setting value
## version R version 4.1.3 (2022-03-10)
## os macOS Monterey 12.2.1
## system x86_64, darwin17.0
## ui RStudio
## language (EN)
## collate en_US.UTF-8
## ctype en_US.UTF-8
## tz Asia/Shanghai
## date 2023-10-27
## rstudio 2023.09.0+463 Desert Sunflower (desktop)
## pandoc 3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
##
## ─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## package * version date (UTC) lib source
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## BiocGenerics * 0.40.0 2021-10-26 [2] Bioconductor
## BiocParallel 1.28.3 2021-12-09 [2] Bioconductor
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## car 3.1-2 2023-03-30 [2] CRAN (R 4.1.2)
## carData 3.0-5 2022-01-06 [2] CRAN (R 4.1.2)
## caTools 1.18.2 2021-03-28 [2] CRAN (R 4.1.0)
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## class 7.3-22 2023-05-03 [2] CRAN (R 4.1.2)
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## cli 3.6.1 2023-03-23 [2] CRAN (R 4.1.2)
## cluster 2.1.4 2022-08-22 [2] CRAN (R 4.1.2)
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## compositions 2.0-6 2023-04-13 [2] CRAN (R 4.1.2)
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## GenomicRanges * 1.46.1 2021-11-18 [2] Bioconductor
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## impute 1.68.0 2021-10-26 [2] Bioconductor
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## memoise 2.0.1 2021-11-26 [2] CRAN (R 4.1.0)
## metagenomeSeq 1.36.0 2021-10-26 [2] Bioconductor
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## NetCoMi * 1.0.3 2022-07-14 [2] Github (stefpeschel/NetCoMi@d4d80d3)
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## viridisLite * 0.4.2 2023-05-02 [2] CRAN (R 4.1.2)
## vroom 1.6.3 2023-04-28 [2] CRAN (R 4.1.2)
## webshot 0.5.5 2023-06-26 [2] CRAN (R 4.1.3)
## WGCNA 1.72-1 2023-01-18 [2] CRAN (R 4.1.2)
## withr 2.5.0 2022-03-03 [2] CRAN (R 4.1.2)
## Wrench 1.12.0 2021-10-26 [2] Bioconductor
## xfun 0.40 2023-08-09 [1] CRAN (R 4.1.3)
## XMAS2 * 2.2.0 2023-10-27 [1] local
## XML 3.99-0.14 2023-03-19 [2] CRAN (R 4.1.2)
## xml2 1.3.5 2023-07-06 [2] CRAN (R 4.1.3)
## xtable 1.8-4 2019-04-21 [2] CRAN (R 4.1.0)
## XVector 0.34.0 2021-10-26 [2] Bioconductor
## yaml 2.3.7 2023-01-23 [2] CRAN (R 4.1.2)
## zCompositions 1.4.0-1 2022-03-26 [2] CRAN (R 4.1.2)
## zlibbioc 1.40.0 2021-10-26 [2] Bioconductor
## zoo 1.8-12 2023-04-13 [2] CRAN (R 4.1.2)
##
## [1] /Users/zouhua/Library/R/x86_64/4.1/library
## [2] /Library/Frameworks/R.framework/Versions/4.1/Resources/library
##
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