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Create a plan for episodes #2

Description

@TuomasBorman

The first task would be to create plan for episodes that are going to be taught in the lesson.

These would be the learning objectives for the lesson:

  1. Importing microbiome data as TreeSummarizedExperiment object.
  2. Identify whether alpha diversity differs between study groups using appropriate diversity metrics and statistical tests.
  3. Interpret beta diversity ordination plots to evaluate differences in microbiome composition between sample groups.
  4. Identify taxa that differ significantly in abundance between study groups using differential abundance analysis.

We could have the following episodes:

  1. Data import to TreeSummarizedExperiment
  2. Alpha diversity
  3. Beta diversity
  4. Differential abundance analysis

... as they cover the typical analysis tasks in microbiome research.

With @HediaTnani, we have already discussed this little bit and concluded something following for the learning objectives for each episode:

  1. Data import to TreeSummarizedExperiment
    • Load the data into R session.
    • Construct TreeSummarizedExperiment object from the data.
    • Access the tables from the slots of the TreeSE object.
    • Subset TreeSE by selecting only specific samples.
  2. Alpha diversity
    • Define alpha diversity and explain its ecological significance in microbial community analysis
    • Calculate alpha diversity metrics
    • Visualize values across samples
    • Apply statistical tests to compare alpha diversity between study groups (non-parametric Wilcoxon or Mann-Whitney test)
    • Define Evenness and Richness
    • Visualize rarefaction curves
    • Calculate alpha diversity indices with rarefaction and visualize them
  3. Beta diversity
    • Perform PCA and visualize results
    • Perform PCoA
    • Perform dbRDA
  4. Differential abundance analysis
    • Perform DAA
    • Visualize results
    • ...

I think the next step is to do more detailed plan on each episode. The plan should include:

  • Detailed structure of the episode
  • What explanation there are
  • What code examples
  • Challenges and exercises

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