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Activity: Statistics of Gene Expression

Instructions

  • Each student will submit the activity individually to Canvas, but students are encouraged to help one another complete the work
  • Complete the Statistics of Gene Expression Activity found in the DataComputing eBook
    • make sure you carefully follow the instructions and mirror the code in the activity as you work
    • every task in the activity should have narrative text describing your observations; most steps also require code chunks and corresponding output.
    • you should make commits in GitHub as you complete the activity
  • submit the completed R Notebook as HTML to Canvas before deadline

Tips

Warning

In the "Probing for a Probe" section, you're introduced to the dplyr::do( ) function... this step is "slow" (i.e. takes a long time). Your code will actually fit a regression model to each of more than 32,000 probes and then store the R-squared for each one of them. In fact, if you understand what it's doing, it happens incredibly fast... but it still takes a long time (i.e., several minutes depending on available computational resources).

Hints

  • Among the "several suggestions for improving the graphic", #3 and #4 will be most handy
  • You'll need to combine elements of previous plots in order to produce Figure 17.5
  • When you reproduce Figure 17.5 for a new Probe in the Your Turn portion, you shouldn't start from scratch. Find code you can copy and paste earlier in the assignment and modify it slightly to change the Probe of interest.

Grading

Assignment is worth a total of 10 points.

  • [5 points] Follow along with the activity in the book and reproduce the following figures as they appear in the book
    - Figure 17.1: A bar chart comparing TOP3A expression in the different tissue types.
    - Figure 17.2: TOP3A expression in the individual cells.
    - Figure 17.3: TOP3A Bar chart with individual cells overlaid
    - Figure 17.4: TOP3A Dynamite plot (bar chart with error bars)
    - Figure 17.5: "Better than Dynamite" (TOP3A expression in the individual cells with overlaid confidence intervals by tissue type)
  • [1 point] recreate Figure 17.6 showing 30 Probes with largest r-squared for expression level explained by tissue type
  • [2 points] Your Turn Choose one probe with high R-squared. Plot expression versus tissue type (like Figure 17.5)
  • [2 points] recreate Figures 17.7 (overlaid density plots) & 17.8 (comparison of highest R^2 from actual data and the Null)

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