bioinfoClass Further Reading

Bioinformatics Class at LLLab

For the whole class

Analysis of single cell RNA-seq data

n this course we will discuss some of the questions that can be addressed using scRNA-seq as well as the available computational and statistical methods avialable. The course is taught through the University of Cambridge Bioinformatics training unit, but the material found on these pages is meant to be used for anyone interested in learning about computational analysis of scRNA-seq data. The course is taught twice per year and the material here is updated prior to each event.

R, ggplot2 and Statistical Foundations r-statistics.co

An educational resource for those seeking knowledge related to machine learning and statistical computing in R. Here, you will find quality articles, with working R code and examples, where, the goal is to make the #rstats concepts clear and as simple as possible.

Data Analysis in Genome Biology

This course introduces algorithms, statistical methods and data analysis programming routines relevant for genome biology. It consists of three main components: lectures, hands-on practicals and student course projects. The lecture topics cover databases, sequence (NGS) analysis, phylogenetics, comparative genomics, genome-wide profiling methods, network biology and more. The hands-on practicals include homework assignments and course projects focusing on data analysis programming of next generation genome data using command-line tools on a computer cluster and the programming environment R.