Important first note: All this material has a copyright holder (myself). Unless otherwise stated, all the materail is under one of the Creative Commons licenses. These licenses give you a lot of freedom to use the material, modify it, etc (read the details of the license for what exactly you can, and cannot, do). So feel free to use this material but, please, give credit where credit is due. (To give you an example, most of the recent material is under a Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license that allows you to freely mix, modify, adapt, and even commercially use this material, but you should give proper attribution and share the modified material with the same licencse).

## Teaching

This is a partial list of some classes I teach at UAM, with links to the PDFs or the original LaTeX (if the LaTeX files are not available here, you can ask me for them).

The PDFs (slides and/or class notes) are always available to our students from the institutional Moodle. But you can't access those unless you are from the Universidad Autonoma de Madrid (UAM). For many courses, I provide here the PDFs or, even better, the public repositories with the original LaTeX or Rnw sources.

### Programming and statistics with R

A one-semester course that is part of the Masters in Bioinformatics and Computational Biology at UAM. We teach R and statistics (at a higher level than the Applied Stats course below). Here is the material for the R part and the stats (with R) part; in the last couple of years we have started devoting 2 to 3 hours to introduce causal inference from observational data ---notes are in the repo, here.

### Applied statistics, in the course Methodology in Molecular Biosciences Research

An intro course to statistics for master's students of the Molecular Biosciences Master. We use R to teach some basic stats (two-sample comparisons and a little bit of linear models). This is the repository for the Rnw files (LaTeX with R) and all data and scripts to produce the PDF.

### Herramientas de programación para bioquímica y biología molecular (Programming tools for biochemistry and molecular biology)

A course for biochemistry and biology bachelors' degree students. We cover Python (taught by Luis del Peso), R, and used to cover a few things about the shell and essential utilities such as sed, grep, etc. This is the github repo with the material (data sets and complete Rnw and scripts to generate the PDFs) for the R part.

### Bioinformática y biología molecular de sistemas, BIBMS (Bioinformatics and molecular systems biology)

A course for biochemistry bachelor's degree students. This is a course taught by several teachers, and I cover phylogenetic inference and statistics for omics. (The PDFs provided are a bundle of three or more files; use your PDF viewer index toolbar or similar to see the full index.) The material for Statistics for omics started being very similar to that in the repo for Stats-bioinfo-intro (full LaTeX/Rnw, etc, sources), but has departed (hopefully, improved) quite a bit.

### Advanced bioinformatics and systems biology

A master's level course that touches on a variety of topics, from HMMs to statistics to phylogenetic inference. The repository for the original LaTeX files. Unfortunately, this course was last taught on 2014-15, and is unlikely to be taught again in the near future.

## Courses about the R statistical computing system

### Current courses

I think I taught my first R course around 2003 at CNIO and not long after that I taught another one at UAM (organized by the “Red temática del CSIC de Bioinformática”). I’ve covered from basic programming and basic stats to specific issues of parallelization or “omics” data analysis.

Most of the R-related courses I've taught recently fall into two categories:

- General intro R programming courses. For example, the material I use for the "Herramientas de programación" bacherlor's degree course, or the annual one-day course I taught for my friends at CNIO. This material is available from the R-bioinfo-intro github repo.
- Intro statistics with R. For example, the material for the "Applied statistics course" (available from the github BM-1 repo), or the very similar (except it is all command-line oriented, so no R Commander or other GUIs) material from the R-basic-stats github repo.
- A few other courses have been much more specific, such as on debugging and parallelization, or longer and covering wider territory, such as courses that covered from programming to generalized linear mixed effects models.

## Miscellaneous talks

### Biclustering, plaid models, et al

This PDF is an old talk about biclustering, with special emphasis on the plaid model of Lazzeroni and Owen, as well as a few other methods (FLOC, xMotif, PRN, OVW, COSA). Much of the material is probably outdated, but the pdf seems to have continued to be of some use to some people, so I am placing it here. There is an R package, biclust, that implements plaid as well as several other methods.