We are all statisticians now

Talk at the Data Intensive Biology Conference in the Johns Hopkins Department of Biology 2014.

Transcript

1. We are all statisticians now
3. N = SAMPLE SIZE
4. N = ($ YOU HAVE) ($ PER SAMPLE)
5. Year $ per (human) Genome
6. rna-seq 2008 N≈2 2010 N≈70 2013 N≈900 PMIDS: 19056941,  20220758,  24092820  
7. www.geni.com
8. http://erlichlab.wi.mit.edu/familinx/index.html
10. https://github.com/jtleek/swfdr
12. research about me blogging teaching
13. jtleek.com about me simplystatistics.org jhudatascience.org
15. from: jtleek@gmail.com Roger let me know you gave him a ballpark figure for the number of students registered for his course "Computing for Data Analysis”. Could you give me an idea of how many have registered for my course "Data Analysis?”    
16. from: pangwei@coursera.org Hi Jeff, 7,000 students! It's pretty awesome. (You'll be able to check this out yourself next week, once the class sites are up.)  
17. from: rdpeng@gmail.com You are f**ed. -roger  
18. 9 classes 1 month long Every month
19. Cumulative Enrollment
20. Dude, we get it data/statistics is everywhere (what is the big deal)
24. what went wrong? 2 things
25. what went wrong? transparency The data/code weren’t reproducible
26. what went wrong? transparency There was a lack of cooperation
27. what went wrong? expertise They used silly prediction rules (Pr(FEC)  =  5/8[Pr(F)  +  Pr(E)  +  Pr(C)]  –  ¼)  
28. what went wrong? expertise They had study design problems (Batch  effects)  
29. what went wrong? expertise Their predictions weren’t locked down Today:  Pr(FEC)  =  0.8   Tomorrow:  Pr(FEC)  =  0.1    
30. At the end of the day the Potti analysis was fully reproducible The problem is that the analysis was wrong
34. hJps://github.com/jtleek/datasharing  
35. Reproducibility = Solved (You’re welcome)
36. um, actually no
37. 1st Discussion Point: Statistical thinking is (often) an afterthought
38. hJp://bit.ly/OgW3xv  
41. hJp://biomickwatson.wordpress.com/2013/04/23/a-­‐guide-­‐for-­‐the-­‐lonely-­‐bioinforma[cian/  
42. Yes, we are witnessing the birth of Yet another “pet bioinformatician”. What I mean by this term is a single bioinformatician employed within a laboratory based group. hJp://biomickwatson.wordpress.com/2013/04/23/a-­‐guide-­‐for-­‐the-­‐lonely-­‐bioinforma[cian/   “ ”
43. 2nd Discussion Point: Most data analysts are untrained
44. One year of biology One year of physics One year of English Two years of chemistry (through organic chemistry) https://www.aamc.org/students/applying/requirements/ med school entrance requirements
45. hJp://www.nejm.org/doi/full/10.1056/NEJMoa1400029  
46. I  am  a  postdoctoral  fellow  in  redacted  group   I  collected  data  on  redacted   …     Preliminary  analysis  has  pulled  out  some  interes[ng   things  but  we  need  some  professional  assistance   …     We  want  to  submit  at  the  end  of  next  month.   To: jtleek@gmail.com
47. 3rd Discussion Point: Statistics is not math (and data analysis isn’t statistics)
48. association between shoe size and literacy
56. 4th Discussion Point: How do we balance skepticism & excitement?
58. http://gking.harvard.edu/files/gking/files/0314policyforumff.pdf
59. 1. Statistical thinking is (often) an afterthought 2. Most data analysts are untrained   3. Statistics is not math (and data analysis isn’t statistics)   4. How do we balance skepticism & excitement?  
60. jtleek.com/talks