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Creating Heatmaps and Clustering in R
Rating: 4.3 out of 5(19 ratings)
128 students

Creating Heatmaps and Clustering in R

A practical course in analyzing data used for heatmaps and finding and visualizing clusters in your data
Last updated 7/2020
English

What you'll learn

  • to create colorful heatmaps showing the relationship between species
  • and also gene expression levels between samples
  • how to cluster species/genes in the data sets

Course content

5 sections20 lectures2h 1m total length
  • Introduction2:04

    Introduction to the course

  • Download and install R Studio2:30

    Download and install R Studio

  • R packages for heatmaps and clustering4:08

    Install R packages needed for generating heatmaps, data clustering and data analysis

  • Installing and using BiocManager4:43

    This video shows you how to install and use BiocManager

  • Installing R Studio

Requirements

  • some knowledge of R

Description

Greetings everybody! My name is Dr. Matthew Cserhati. I have a PhD in bioinformatics, and also a BSc in computer science from the University of Szeged, Hungary. I have 18 years of programming experience and have 15 peer-reviewed publications in PubMed. I work at a biotech company where I make daily use of my bioinformatics skills.

In this course the student will be able to use clustering methods to find clusters in his data. He will also be able to make nice-looking heatmaps using the heatmap and the pheatmap command. Clustering topics such as k-means clustering, PAM clustering, silhouette plots, and elbow plots will be covered. Theoretical background behind the clustering algorithm will be provided. Besides this there will also be multiple practice lessons using real data.

Minimal familiarity with R coding is required. The figures you make here can be used for publication purposes. The tools that you learn here can be very valuable in your research toolkit. Students from biology, math, physics, geology, medicine are all welcome.

If you are interested, also check out my courses on kraken2 database programming and using bioinformatics tools in covid research, also available here on Udemy.

Have a nice day and happy coding!


Who this course is for:

  • college biology students
  • biology/bioinformatics researchers