8.6 Try it Question 3 - Does gender contribute to individual microbiome variation
The biological sex of the host has been suggested to help shape or influence its gut microbiome. Some candidate microbes have been implicated in sex differences. Here we will explore the potential sex-based differences in the human gut microbiome.
Approach: First survey the differences in microbiome across gender at the level of phyla and species, and identify potential candidates that may differ between males and females. Then, plot your candidates of interest and additional candidate microbes previously associated with gender-based variation.
8.6.0.1 Step 3A. Perform an initial survey to see if there are any differences in phyla and species composition between genders.
Specifically, your plot should show phyla diversity within male and female groups.
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 = "fill in the blank") +
geom_bar(aes(color = fill in the blank, fill = fill in the blank), stat = "identity", position = "stack")| 3A-1. Insert the resulting plot below: |
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Consider any initial differences you see, then choose one high-abundant and one low-abundant candidate Phylum that shows hints of being differentially abundant between genders.
| 3A-2. Record the phylum you chose: |
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8.6.0.2 Step 3B. Test gender-based difference in Species for the high abundant phylum you selected. Specifically, your plot should show species diversity within male and female groups for only your phylum of choice.
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 starter:
subset = subset_taxa(miso, Phylum == "fill in the blank")
plot_bar(subset, "fill in the blank", 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"))- 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.
| 3B-1. Insert the resulting plot below: |
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| 3B-2. Do you observe any differences in species based on gender within your highly abundant phylum? |
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8.6.1 Step 3C. Test gender-based difference in Species for the low abundant phylum you selected.** Specifically, your plot should show species diversity within male and female groups for only your phylum of choice.
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 code you used in Step 3B as a template for your code
You may receive an error if you chose a phylum that has no species data (all NA). Please choose a new low abundant phylum and try again.
| 3C-1. Insert the resulting plot below: |
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| 3C-2. Do you observe any differences in species based on gender within your low abundant phylum? |
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8.6.3 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).