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Authors: Jessica Kirkpatrick krkptrc...  or Boris Steipe 

Exploratory Analysis of Biological Data using R 2018

Course covered for this workshop are broadly relevant for many areas of modern, quantitative biology such as flow cytometry, expression profile analysis, function prediction and more.

Introduction to R 2018

Course introduces essential ideas and tools of R, and covers statistical tests in R.

Exploratory Analysis of Biological Data using R 2017 Module 5-Hypothesis Testing

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 4-Clustering

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 3-Dimension Reduction

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 2-Regression

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 1-Exploratory Data Analysis

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Introduction to R 2017

Course covers the bioinformatics tools available for meeting the challenges of data handling and breaking down problems into structured parts using R.