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Rafael Irizarry and I have been working on a free online course, Data Analysis for Genomics (PH525x) which starts on April 7, 2014 and runs for 8 weeks:
Our target audience are postdocs, graduate students and research scientists that are tasked with analyzing genomics data, but perhaps do not have formal training. The course will start with the very basics, but will ramp up rather quickly and end with workflows for genome variation, RNA-seq, DNA methylation, and ChIP-seq.
The class consists of lectures and computer labs. The lectures cover foundational topics such as exploratory data analysis, basic statistical inference, linear regression, modeling with parametric distributions, empirical Bayes, multiple comparison corrections and smoothing techniques. The labs will run parallel to the lectures and use R/Bioconductor to explore and analyze genomics data. The lecture and the labs have accompanying R markdown files for reproducing plots and analyses, which we will link to each week (in a few weeks we will also have a complete repository of all the Rmd files).
Our target audience are postdocs, graduate students and research scientists that are tasked with analyzing genomics data, but perhaps do not have formal training. The course will start with the very basics, but will ramp up rather quickly and end with workflows for genome variation, RNA-seq, DNA methylation, and ChIP-seq.
The class consists of lectures and computer labs. The lectures cover foundational topics such as exploratory data analysis, basic statistical inference, linear regression, modeling with parametric distributions, empirical Bayes, multiple comparison corrections and smoothing techniques. The labs will run parallel to the lectures and use R/Bioconductor to explore and analyze genomics data. The lecture and the labs have accompanying R markdown files for reproducing plots and analyses, which we will link to each week (in a few weeks we will also have a complete repository of all the Rmd files).
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