Class Journal Week 8

Nicole Anguiano

1. What were the main issues with the data and analysis identified by Baggerly and Coombs? What best practices enumerated by DataONE were violated? Which of these did Dr. Baggerly claim were common issues?
2. What recommendations does Dr. Baggerly recommend for reproducible research? How do these correspond to what DataONE recommends?
3. Do you have any further reaction to this case after viewing Dr. Baggerly's talk?
4. Go back to the Merrell et al. (2002) paper and look at your "sanity check" where you compared the fold changes and p values for certain genes between your work and the paper. Did the values match? Why do you think that is? Do you think there is sufficient information there for you to reproduce their data analysis? Why or why not?

Nanguiano (talk) 15:06, 20 October 2015 (PDT)

Jake Woodlee

1. What were the main issues with the data and analysis identified by Baggerly and Coombs? What best practices enumerated by DataONE were violated? Which of these did Dr. Baggerly claim were common issues?
2. What recommendations does Dr. Baggerly recommend for reproducible research? How do these correspond to what DataONE recommends?
3. Do you have any further reaction to this case after viewing Dr. Baggerly's talk?
4. Go back to the Merrell et al. (2002) paper and look at your "sanity check" where you compared the fold changes and p values for certain genes between your work and the paper. Did the values match? Why do you think that is? Do you think there is sufficient information there for you to reproduce their data analysis? Why or why not?

Jwoodlee (talk) 15:35, 22 October 2015 (PDT)

Emily Simso

1. What were the main issues with the data and analysis identified by Baggerly and Coombs? What best practices enumerated by DataONE were violated? Which of these did Dr. Baggerly claim were common issues?
   • The most common issues are that, first, documentation is often poor in clinical trials, thus not explaining what researchers did in their work. There are also then problems with intuition, since people assume things about the data. Overall, Baggerly and Coombs stress that lack of thoroughness with data and research leads to complications further on.
   • The violated best practices according to DataONE were: consistency, being descriptive, and lacking data or information.
2. What recommendations does Dr. Baggerly recommend for reproducible research? How do these correspond to what DataONE recommends?
   • Dr. Baggerly recommends that groups use the same standards for reports, templates are reused, there is a report structure for approval, and use executive summaries for complete documentation.
   • This connects to DataONE because they stress reproducible research through appropriate file types, consistent formatting, clear definitions, and understanding how databases are set up before using them, amongst other points.
3. Do you have any further reaction to this case after viewing Dr. Baggerly's talk?
   • I think watching Dr. Baggerly's talk helped explain how something like the Duke case could happen, because there are so many details in data and research. It seems that mistakes could easily be covered up simply because there is a culture of not documenting every aspect of your work. I think that this needs to change so that future clinical trials are more closely regulated.
4. Go back to the Merrell et al. (2002) paper and look at your "sanity check" where you compared the fold changes and p values for certain genes between your work and the paper. Did the values match? Why do you think that is? Do you think there is sufficient information there for you to reproduce their data analysis? Why or why not?
   • The values did not match between the Merrell et al. analysis and my analysis. This is probably because they are much more trained in this field and have more resources at their disposal. They were also able to perform more tests on the data, whereas we only had the given values. While I think we are able to get fairly accurate results, we are not close enough to the experiment to get the exact same results.