Skip to content

Materials for 12-day course on analyzing RNA-Seq, ChIP-Seq and variant calling data.

Notifications You must be signed in to change notification settings

Atemia/In-depth-NGS-Data-Analysis-Course

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

36 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

In-depth NGS Data Analysis Course

This branch (May 2017) of the NGS course repo contains all course materials for the Summer 2017 version of HBC's In-depth NGS Data Analysis Course, a 12-day course run over 6 weeks (May 31 through July 7, 2017).

The course is aimed at bench biologists who are interested in learning about NGS-based genomic analysis. The topics covered in-depth during this course are analysis of RNA-Seq and ChIP-Seq data, with an optional Variant Calling session. The sessions will also include functional analysis downstream of sequence data processing. During this course, participants will gain skills in the areas of:

  • UNIX and basic shell scripting
  • high-performance compute clusters, and
  • R for statistical analysis and data visualization.

At the end of this course, participants can expect to have the expertise to independently run data analysis for sequencing experiments.

No prior programming experience or command-line training is required.

This repo contains the materials for the six sessions of the course. The six sessions are described below:


NOTE: Additional materials are included in this repo but are not part of the main course.


These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

About

Materials for 12-day course on analyzing RNA-Seq, ChIP-Seq and variant calling data.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • HTML 97.5%
  • Shell 2.5%