8.5 Try it Question 2 - What are some of the most abundant microbes when viewed at different taxonomic resolutions
Microbes within the core microbiome - the most common and abundant species across samples in a given group - are likely to be involved in key functions of the holobiont. Here we will explore some of the most common microbes at increasing levels of taxonomic resolution.
Approach: Plot progressively lower level taxa for all individuals, subsetting most abundant from each rank.
8.5.1 Step 2A. Plot Phyla across all subjects and identify the most abundant Phyla. Specifically, your plot should show Phyla diversity across all 21 individuals.
Refer to the “Explore 16S rRNA Data with phyloseq” tutorial for help using the plot_bar() function.
Use the following code as a template:
plot_bar(miso, "fill in the blank", fill = "fill in the blank", title = "choose a name for your graph") +
geom_bar(aes(color = fill in the blank, fill = fill in the blank), stat = "identity", position = "stack")| 2A-1. Insert the resulting plot below: |
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| 2A-2. Enter the name of the most abundant Phyla below: |
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8.5.2 Step 2B. Subset the most abundant Phyla, and plot Order (Skip Class)
Refer to the “Subset taxonomy” section of the “Explore 16S rRNA Data with phyloseq” tutorial for help using the subset_taxa and plot_bar() functions.
Use the following code as a template:
subset = subset_taxa(miso, Phylum == "fill in the blank")
plot_bar(subset, "subject", fill = "Order", title = "choose a name for your graph") +
geom_bar(aes(color = fill in the blank, fill = fill in the blank), stat = "identity", position = "stack")| 2B-1. Insert the resulting plot below. Your plot’s abundance should be more varied and less than all the previous plots you have made so far, as it is only including a subset of the overall dataset. |
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| 2B-2. Enter the name of the most abundant Order of your chosen phylum below: |
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8.5.2.1 Step 2C. Subset the most abundant Order, and plot associated Family
Refer to the “Subset taxonomy” section of the “Explore 16S rRNA Data with phyloseq” tutorial for help using the subset_taxa and plot_bar() functions.
Use the following code as a template:
subset = subset_taxa(miso, Order == "fill in the blank")
plot_bar(subset, "subject", fill = "Family", title = "choose a name for your graph") +
geom_bar(aes(color = fill in the blank, fill = fill in the blank), stat = "identity", position = "stack")| 2C-1. Insert the resulting plot below: |
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| 2C-2. Enter the name of the most abundant Family below: |
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8.5.2.2 Step 2D. Subset most abundant Family, and plot associated Genus
Refer to the “Subset taxonomy” section of the “Explore 16S rRNA Data with phyloseq” tutorial for help using the subset_taxa and plot_bar() functions.
Use the following code as a template:
subset = subset_taxa(miso, Family == "fill in the blank")
plot_bar(subset, "subject", fill = "Genus", title = "choose a name for your graph") +
geom_bar(aes(color = fill in the blank, fill = fill in the blank), stat = "identity", position = "stack")| 2D-1. Insert the resulting plot below: |
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| 2D-2. Enter the name of the most abundant Genus of your chosen Family below: |
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8.5.2.3 Step 2E. Subset the most abundant Genus, and plot associated Species
Refer to the “Subset taxonomy” section of the “Explore 16S rRNA Data with phyloseq” tutorial for help using the subset_taxa and plot_bar() functions.
Use the following code as a template:
subset = subset_taxa(miso, Genus == "fill in the blank")
plot_bar(subset, "subject", fill = "Species", title = "choose a name for your graph") +
geom_bar(aes(color = fill in the blank, fill = fill in the blank), stat = "identity", position = "stack")+
theme(legend.text=element_text(size=6)) +
theme(legend.key.size = unit(6, "pt"))- Note, given the many different Species associated with an abundant Genus, we may need to reduce the legend text and key size in order to visualize the plot better. We have added some code above to help see the legend.
| 2E-1. Insert the resulting plot below: |
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| 2E-2. Enter the name of the some of the most abundant species below: |
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| 2E-3. After looking through all your plots, summarize your conclusion regarding individual microbiome composition diversity. Explain what reasoning led you to your conclusion. |
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| 2E-4. If an ASV is listed as NA at a given taxonomic rank, it means taxonomic information is not available at that level for that microbe. Are there are lot of ASVs with NA annotations across different levels? |
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| 2E-5. Look up one of the species you found. How might it serve a function in the gut microbiome? |
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8.5.3 Grading criteria
- Download the assignment to your local computer as a .docx, complete it, and upload the assignment to your LMS (Blackboard, Canvas, Google Classroom).