Online tutorials for bioinformatics and others
Here are the lists of useful tutorials, mostly are about array and sequencing analysis. And I will update it when I am available.
Bioinformatics
- Bioinformatics Team of U Texas, wide topics included, need some understanding of what you want to learn.
- UC Davis Bioinformatics Training Program. NGS, array, and R. I suggest this data analysis and visualization course, focusing on bioinformatics analysis by R.
- A microarray course from MD Anderson (last updated in 2010).
- HOMER. Yes, HOMER is an NGS software. But the authors do really provide great toturials about NGS, covered most fields.
- Slides of workshop lecutures from BioTech Institute of Cornell. About Linux, programming, and of course, NGS.
- Statistical Bioinformatics provided by John R. Stevens of Utah State University.
- Learn about Bioinformatics and Computational Tools for Biology, some lectures from Whitehead Institute of MIT. Some contents are at submenu. I found this page because I found they provided a lecture for our ngs.plot.
- A bioinformatics tutorial provided by Assotiate Professor Dr. Tzu Lip Phang from UC Denver.
- CUBELP2. Dr Robert King’s collection about bioinformatics tutorials, :-)
- RNA-seqlopedia A good resource for RNA-seq.
Genetics & Genomics
As I was trained in evolutionary genetics (of primates), I am always interested about the topics in this fields.
- Human genetics course from Mark Batzer’s lab of LSU.
- Introduction to Statistical and Computational Genomics, from William Noble of Washington University, based on Python.
Computer science, statistics, or other
Machine learning
- Free book: An Introduction to Statistical Learning, another book (for entry level) of the authors of the famous book The Elements of Statistical Learning.
- Free book: Neural Networks and Deep Learning, written by Michael Nielson.
- Free book: A Course in Machine Learning, written by Hal Daumé III.
- Data mining (in R) course from Ryan Tibshirani of CMU.
- Free book: Probabilistic Programming & Bayesian Methods for Hackers, mainly written by Cam Davidson-Pilon.
- Introduction for Machine Learning A course provided by J. Jeffry Howbert of Washington University.
R
- Free book: R cookbook, written by Winston Chang.
- Computing with data, provided by Steven Buechler, University of Notre Dame.
Misc
- Free book: Probabilistic Models of Cognition, written by Noah D. Goodman and Joshua B. Tenenbaum.