Analyzing Genomic Data in R

Track Description

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.

Prerequisites

There are no prerequisites for this track

Course
1
Introduction to Bioconductor in R
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Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!
Course
2
RNA-Seq with Bioconductor in R
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Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.
Course
3
Differential Expression Analysis with limma in R
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Learn to use the Bioconductor package limma for differential gene expression analysis.
Learn to use the Bioconductor package limma for differential gene expression analysis.
Course
5
ChIP-seq with Bioconductor in R
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Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.
Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

Frequently asked questions

Is this Track suitable for beginners?

Yes, this Track is designed for beginners in bioinformatics. Although some basic knowledge of the R programming language is recommended, the Track will include detailed step-by-step instructions on how to use Bioconductor and install the essential packages.

What is the programming language of this Track?

This Track uses the R programming language.

Which jobs will benefit from this Track?

This Track will provide an introduction to bioinformatics and positions such as bioinformaticians, data scientists, and computational biologists will benefit from this Track.

How will this Track prepare me for my career?

This Track will provide an introduction to bioinformatics and data analysis software specifically designed for the bioinformatics domain. It will cover topics such as chip-sequencing data, differential expression analysis and RNA sequencing. This Track will help prepare you for future roles in bioinformatics.

How long does it take to complete this Track?

This Track usually takes 16 hours to complete as it consists of several courses that significantly upskill users.

What's the difference between a skill track and a career track?

A skill track focuses on building domain-specific skills and provides real-world exercises and datasets. A career track is focused on helping users better prepare for a specific job or career path and offers mentorship and opportunities to apply for job roles.

Analyzing Genomic Data in R

Track Description