Gene expression data analysis using R

How to make sense out of your RNA-Seq/microarray data

Introduction & target audience
Five days hands-on computer course for biological and clinical researchers whose research involves experiments that generate gene expression data. The course focuses on microarray and next-generation sequencing gene expression data, but some concepts may be applicable to other types of genomics data. Most of the speakers (and therefore examples) have a biomedical background. Software packages used are freeware, including the statistical software R, Bioconductor, Cytoscape and web tools. The total number of participants is limited to 40.

Date: July 4-8, 2016

Pre-requisites for participants
Participants need to know what a microarray experiment is, and have their own expression profiling data. They have preferably followed an introduction to R course as a preparation; alternatively they have practiced the “Getting started in R” practical prior to the course. Basic statistical concepts including mean, variance, standard deviation, probability distributions, t-test, p-value, correlation, and linear regression are assumed known. These are typically seen during basic statistics courses.

More information via Molmed website

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