Analyzing Genomic Data in R

Are you interested in analyzing next-generation sequencing data but lacking in strong computational skills? In this skills track, geared towards non-computational biologists, you will learn to use Bioconductor, the specialized repository for bioinformatics software, along with essential Bioconductor packages. Then, you'll learn about current best-practice workflows for RNA sequencing differential expression analysis, as well as Chip-sequencing data.

R16 hours4 Courses

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Introduction to Bioconductor in R

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

4 hours

RNA-Seq with Bioconductor in R

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

4 hours

Differential Expression Analysis with limma in R

Learn to use the Bioconductor package limma for differential gene expression analysis.

4 hours

ChIP-seq with Bioconductor in R

Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

4 hours

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Join over .css-1osvizq-TrackShowPage{color:#03ef62;}11,670,000 learners and start Analyzing Genomic Data in R today!

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Join over 11,670,000 learners and start Analyzing Genomic Data in R today!