A hands on course on Statistics for heterogeneous biological data

(Sequences, images, clinical data, mRNA, single cell measurements, ..) using R and many Bioconductor packages.

Course Schedule

Live lectures are at 1:30pm PST to 2:50pm on Mondays and Wednesdays in Room 203 in building 200 called the History Corner.

Lecture readings need to be done before the lecture time.

Weekly Labs will be done either on your own or during Lab sessions run by the Teaching Team.

Here is the sketch of the schedule, it may change when the survey results of preferred topics comes in.

Date Topic
Wednesday 27 Sept Introduction (covering: book chapter introduction and chapter 1; lecture 1)
Monday Oct 2 Bioconductor, Reproducibility and Simulations (covering: book chapter 1 & 2; lectures 1 & 2)
Wednesday Oct 4 Models and Simulations (covering: book chapter 1 & 2; lectures 1 & 2)
Monday Oct 9 Graphics (covering: book chapter 3; online lecture 3)
Wednesay 11 Oct Statistics, Mixture Models and Variance Stabilization (covering: book chapter 2, 4; lecture 4)
Monday Oct 16 Clustering (covering: book chapter 5; lecture 5)
Wed Oct 18 Testing and RNA-Seq (covering: book chapters 6 & 8; lectures 6 - 8)
Monday Oct 23 Multivariate Analysis (covering: book chapter 7; lectures 9 & 10)
Wed Oct 25 RNA seq and GLMs
Monday October 30 Ordination, CA, NMDS (book chapter 9).
Wednesday Nov 1 Networks, graphs and phylogenetic trees (book chapter 10
Monday Nov 6 Microbial ecology; denovo, denoising abundance testing and multi-table methods
Wednesday Nov 8 Supervised Learning methods for heterogeneous data (book, chapter 12).
Monday Nov 13 Embeddings and nonlinear pseudo-time manifold learning
Wednesday Nov 15 Single Cell Video Lecture SingleCellExperiment
Monday Nov 27 Guest Lecture: Complex data integration, Professor Engelhardt
Wednesday Nov 29 Working with image data (book, chapter 11)
Monday Dec 4 Experimental design, analysis good practice (book, chapter 13), computational tools
Wednesday Dec 6 Reproducible research : next steps for publication and research

Labs and Office Hours

Instructor Day Time Location
Susan Holmes Monday 3- 5pm Bowker/Sequoia 207
Paula Gabenz Friday 3 - 5pm
Yu Wang Thursday 1 - 3pm

The book

The book for the course is available on Amazon and Cambridge University Press

It is also available for free online at both Stanford and EMBL.

The data are all available together as a large compressed tar file