Track
Analyzing Genomic Data in R
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Analyzing Genomic Data in R
Prerequisites
There are no prerequisites for this trackCourse
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!
Course
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.
Course
Learn to use the Bioconductor package limma for differential gene expression analysis.
Course
Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.
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FAQs
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.
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