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Radboud Summer Course 7/2021 https://www.ru.nl/radboudsummerschool/courses/2021/brain-bacteria-behaviour/

License: Other

R 7.95% TeX 91.02% CSS 1.03%

course_2021_radboud's Introduction

microbiome R package


Join the chat at https://gitter.im/microbiome/microbiome Build Status codecov.io PRs Welcome Watch on GitHub Star on GitHub install with bioconda


NOTE While we continue to maintain this R package, the development has been discontinued as we have shifted to supporting methods development based on the new TreeSummarizedExperiment data container, which provides added capabilities for multi-omics data analysis. Check the miaverse project for details.

Tools for the exploration and analysis of microbiome profiling data sets.

This R package extends the phyloseq data container. The package is actively maintened but we have discontinued the development and shifted to support methods development based on the (Tree)SummarizedExperiment data containers, see microbiome.github.io for more details.

Installation and use

See the package tutorial.

Kindly cite as follows: "Leo Lahti, Sudarshan Shetty et al. (Bioconductor, 2017). Tools for microbiome analysis in R. Microbiome package version 1.23.1. URL: http://microbiome.github.com/microbiome. See also the relevant references listed in the manual page of each function.

Contribute

Contributions and feedback are very welcome:

Publications using the microbiome package

Below some publications that utilize the tools implemented in this package. The list of publications is not exhaustive. Let us know if you know of further publications using the microbiome package; we are collecting these on the website.

Intestinal microbiome landscaping: Insight in community assemblage and implications for microbial modulation strategies. Shetty S, Hugenholtz F, Lahti L, Smidt H, de Vos WM, Danchin A. FEMS Microbiology Reviews fuw045, 2017.

Metagenomics meets time series analysis: unraveling microbial community dynamics Faust K, Lahti L, Gonze D, de Vos WM, Raes J. Current Opinion in Microbiology 15:56-66 2015.

Tipping elements in the human intestinal ecosystem Lahti L, Salojärvi J, Salonen A, Scheffer M, de Vos WM. Nature Communications 5:4344, 2014.

Fat, Fiber and Cancer Risk in African, Americans and Rural Africans O’Keefe S, Li JV, Lahti L, Ou J, Carbonero F, Mohammed K, Posma JM, Kinross J, Wahl E, Ruder E, Vipperla K, Naidoo V, Mtshali L, Tims S, Puylaert PGB, DeLany J, Krasinskas A, Benefiel AC, Kaseb HO, Newton K, Nicholson JK, de Vos WM, Gaskins HR, Zoetendal EG. Nature Communications 6:6342, 2015.

Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data Lahti L, Salonen A, Kekkonen RA, Salojärvi J, Jalanka-Tuovinen J, Palva A, Orešič M, de Vos WM. PeerJ 1:e32, 2013.

The adult intestinal core microbiota is determined by analysis depth and health status Salonen A, Salojärvi J, Lahti L, and de Vos WM. Clinical Microbiology and Infection 18(S4):16 20, 2012.

Acknowledgements

Main developer: Leo Lahti

Main co-authors: Sudarshan Shetty

Contributors

Thanks for [@johanneskoester] and [@nick-youngblut] for contributing Bioconda installation recipe.

The work has been supported by the following bodies:

This work extends the independent phyloseq package and data structures for R-based microbiome analysis.

course_2021_radboud's People

Contributors

antagomir avatar chouaibb avatar henrikeckermann avatar tuomasborman avatar

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course_2021_radboud's Issues

Differential abundance to OMA

OMA is missing examples on differential abundance analysis entirely.

I propose to copy or move all/most examples from the course material differential abundance section to OMA.

After this, the section in the Radboud material can be simplified, and the OMA cited for more examples.

This will also give us a good start for extending the OMA with respect to various differential abundance methods.

Information missing from PDF version

I think it would be nice to have also PDF version, if someone wants to download the material. PDF version can be opened from the top of html version (pdf icon).

However, some code and tables are too wide, so that they don't fit to page. html version is on higher priority, so it's better to not make any modifications directly to the code, because that would modify also the html version.

So, if we want also the pdf version, is there any options to modify only the pdf version, so that it would contain all the information? Maybe some parameters to _output.yml file like gitbook has?

-Tuomas

Data import example

The example on importing biom files in R could be moved from course page to OMA book using the same or different example data.

Then the course material should still provide link to Tengeler et al. 2020 data set (specific for the course), and link to OMA for an example on how to import such biom files. The course participants can then connect the pieces and work our data import part on their own using these two resources (link to Tengeler data folder + biom import example from OMA book).

PCoA with continuous colors

Using Shannon diversity in the examples is confusing, let us switch to continuous metadata variable (age, bmi, diet..?)

  • For later courses

Run the Wilcoxon test for each of the taxa ranks

Hi, I'm comparing a set of biological samples that are classified into two groups of interest called "Status" (1 and 0). I had the following phyloseq object:

mirl_phyloseq_final
phyloseq-class experiment-level object
otu_table() OTU Table: [ 8229 taxa and 42 samples ]
sample_data() Sample Data: [ 42 samples by 6 sample variables ]
tax_table() Taxonomy Table: [ 8229 taxa by 6 taxonomic ranks ]

Then I agglomerated it by family:
mirl_phyloseq_final.family=tax_glom (mirl_phyloseq_final, taxrank="Family")

mirl_phyloseq_final.family
phyloseq-class experiment-level object
otu_table() OTU Table: [ 364 taxa and 42 samples ]
sample_data() Sample Data: [ 42 samples by 6 sample variables ]
tax_table() Taxonomy Table: [ 364 taxa by 6 taxonomic ranks ]

And then merged it with psmelt:
melted.f=psmelt (mirl_phyloseq_final.family)
So, I got a data.frame (melted.f) with the samples, the found ASVs, the abundance of each one, and the taxonomic classification agglomerated by family that looks like this:
abundance

If I want to calculate the differential abundance between the two groups and run Wilcoxon for a family, I do the following:
wilcox.test (Abundance~Status, data=melted.f[which(melted.f$Family=="Mycoplasmataceae"),]).
And I obtain a p-value.
My intention is to run the Wilcoxon test to calculate differential abundance between the two groups of samples, for all families (in a loop or something like) this and then store those p-values in a data frame as was done in: https://microbiome.github.io/course_2021_radboud/differential-abundance-analysis.html

Any idea how I can do it?

4/5.2.1 rowData (taxonomic information)

This subsection has kable table. In html view the table is cut from the right. It could be possible to have a slider that allows the user to see the whole table if needed. Is this possible to include easily in bookdown?

Side menu dropdown

Is it possible to make the subchapters as a drop-down option in the sidebar menu at the course page? The number of subchapters is now so high that the side bar becomes too populated and unclear.

Citation and solutions problem

Hi,

I noticed that

  1. Exercise solutions' html versions do not work. Should there be html versions?

  2. Citation in the last page is weird. I think it is done automatically, but I'm not sure where, in Github Action?
    image

  3. 10 Study material still includes 10.2 Example solutions subchapter even though there is already chapter 12 Exercise solutions. Subchapter should be deleted?

-Tuomas

automating the rendering via GA

The OMA book is automatically rendered to HTML after Rmd modification.

This happens through Github Actions.

We could add the same automation here, in order to save some extra effort with manual rendering?

For details on how to do, check OMA.

Additional resources section

Can we add the following links in material.md (I will then pick these up and use in some other parts of the text also). Some of this you may readily find from the OMA book introduction section.

  • SummarizedExperiment: link to the R/Bioconductor project page, and to the original publication
  • TreeSummarizedExperiment: link to the R/Bioconductor project page, and to the original publication
  • SingleCellExperiment: link to the R/Bioconductor project page, and to the original publication

Add question / example on TSE -> phyloseq conversion

Important as there are still many tools that work with phyloseq.

@HenrikEckermann could you make sure if both our demo data sets (open and proprietary one) can converted to phyloseq object? We could add an example Rmd file in the training material so that it is available as a model solution if someone needs it and cannot solve on his/her own.

Hiding sections

Is there a way to hide sections from the sidebar menu? I would like to keep the beta diversity Aitchison examples as additional material that I could add during the course, or by providing a link.

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