RNAseq Analysis using R

Overview

This module teaches you to use various R-based tools for RNAseq data analysis. You will learn about mapping (kallisto), differential expression analysis (DESeq2, edgeR, sleuth), annotation, clustering, GO analysis and other biological inference procedures.

Details

RNAseq is a major application of high-throughput sequencing technologies (NGS), but researchers in biology often struggle with its data analysis component. This module teaches you to use various R-based tools for RNAseq data analysis. You will learn about mapping (kallisto), differential expression analysis (DESeq2, edgeR, sleuth), annotation, clustering, GO analysis and other biological analyses of data.

Topics

  1. Counting using kallisto
  2. Merging results and annotation using dplyr,
  3. Differential expression analysis (DESeq2, edgeR, limma-voom, sleuth),
  4. Clustering and heatmap plots,
  5. Annotation process,
  6. GO analysis.

Cost

$99 for premium members, $125 for others.

Class Style

The classes will be conducted through online interactive chat session.

Testimonials

You can read the testimonials for our summer R classes here.

Register

Please sign up for the module at the following link. At present no payment is necessary to register.

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