Professors Susan Holmes and Wolfgang Huber
TA : Nikos Ignatiadis
Dates and location
- 30 September 2019 to 18 October 2019.
- Lectures are at 10.30am are 1.5 hours long for 3 weeks, see schedule here
- Labs are not compulsory and are given three afternoons a week 1:30 PM - 2:50 PM.
This is a three unit class open to Stanford students, undergraduates can receive WIM credit by taking it as Stats 155, graduate students take it for 1-3 credits as Bios 221 or Stats 366.
Tentative Syllabus
- 1 - Generative probabilistic models for biological data, Introduction to Bioconductor
- 2 - Statistical analysis of data; simulations, Monte Carlo and maximum likelihood
- 3 - Mixture models ; bootstrapping
- 4 - High quality graphics and visualization of large, heterogeneous data; the grammar of graphics and ggplot2
- 5 - Multiple hypothesis testing
- 6 - Multivariate analyses, PCA, SVD, et al.
- 7 - RNA-seq and linear models
- 8 - Cluster analyses : finding latent groupings (ex:cytoF data).
- 9 - RNA-seq revisited: single cell, Gamma-Poisson distribution, shrinkage
- 10 - Multi-domain, multitable, multi-omics data.
- 11 - Networks, graphs and phylogenetic trees
- 12 - Working with image data
- 13 - Microbial ecology; abundance testing
- 14 - Supervised Learning methods for heterogeneous data.
- 15 - Experimental design, analysis good practice, good use of computational tools
The syllabus will be adapted to the audience.
Through the course, you will get acquainted with over 25 R and Bioconductor packages.
Commitment to the class
Because of the high demand for spots in the class, we can only take students who can commit to the full program, ie about 5 hours a work every day from September 30th until October 18th.
Course Schedule
Because of difficulties scheduling a room due to the Medical School’s room scheduling:
| Day | Date | Morning | 10:30AM-11:50AM | Afternoon | 1:30-2:50PM |
|---|---|---|---|---|---|
| Mon | 2019-09-30 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Tue | 2019-10-01 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | No Lab |
| Wed | 2019-10-02 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Thu | 2019-10-03 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Fri | 2019-10-04 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | No Lab |
| Mon | 2019-10-07 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Tue | 2019-10-08 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | No Lab |
| Wed | 2019-10-09 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Thu | 2019-10-10 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Fri | 2019-10-11 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | No Lab |
| Mon | 2019-10-14 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Tue | 2019-10-15 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | No Lab |
| Wed | 2019-10-16 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Thu | 2019-10-17 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | LK 120 |
| Fri | 2019-10-18 | 10:30AM-11:50AM | Alway M114 | 1:30-2:50PM | No Lab |
See the complete schedule here
Prequisites: Working knowledge of R
For instance:
A class that uses R
(Bios 205, Stats 101, Stats 141, Stats 191, Stats 202, Stats 216, …)
Or take the short introductions online available here:
Useful introductory course is the edX course from Harvard taught by Professor Rafa Irizarry
The book
The book for the course is available on amazon here, from Cambridge University Press (use the coupon SHOLMES2018 for a 20% discount) and it is available for free online.
The data are all available together as a large compressed tar file and will soon be available as an R package.