Reproducibility bootcamp day 3 - statistical aspects for reproducible research

Schedule:

8:45 - 9:00 Breakfast

9:00 - 10:30 Statistical inference I

10:30 - 10:50 Coffee break

10:50 - 12:00 Statistical inference II and plotting

12:00 - 1:30 Lunch

1:30 - 3:00 Reproducible reporting I - R Markdown and Batch effects

3:00 - 3:30 Coffee break

3:30 - 5:00 Reproducible reporting II - workflowr

Software installation:

• Run this code in R studio console to install the required packages for R Markdown practice.

Materials:

1. Proper statistical inference: correct use of p-values and correlation (slides)

2. Plots to avoid (slides)

3. Tools for generating reproducible reporting: R markdown and workflowr (slides)

4. Practice: a case study on batch effects

• Exercise
• R code
• Report 1 html
• R markdown for Report 1
• Report 2 html

Resources:

1. R Markdown by R studio

2. workflowr webpage, (a simple example) and ([a more complicated example]https://jdblischak.github.io/singleCellSeq/analysis/)

3. DataCamp course website

4. eBook: Biomedical Data Science by Rafael Irizarry and Michael Love

Some reference papers:

1. p-value and irreproducibility: Halsey, et al. (2015)
2. Assessing reproducibility: Li, et al. (2011)
3. A case study on batch effects:

• Spielman, et al. (2007)
• Akey, et al. (2007)