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Training program description:

The training team at the Harvard Chan Bioinformatics Core provides bioinformatics training in multiple formats, they can be broadly divided into the following:

  1. Introduction to Next-Generation Sequencing (NGS) analysis series
  2. Current topics in bioinformatics series

Our current workshops and courses are designed to help biologists become comfortable with using tools to analyse high-throughput data. We are slowly beginning to expand this repertoire to include training for researchers with more advanced bioinformatics skills.

See our current workshop schedule on our training website.

Introduction to Next-Generation Sequencing (NGS) analysis series:

This series of workshops is divided into 2 categories, Basic Data Skills and Advanced Topics. The Basic workshops serve as the foundation that participants can build upon in the Advanced workshops and we will be offering these as pairs with the appropriate basic workshop preceding and advanced one. Please see below for a description of workshops under each of these 2 categories.

Basic Data Skills:

These workshops provide an introduction to computational skills required for someone to get started with analyzing high-throughput sequencing data independently. These have no prerequisites and do not require any prior experience with programming.

Topic and Link(s) to lessons Prerequisites
Introduction to the command-line interface (shell) None
Introduction to R None
Introduction to R (video tutorials) None

Advanced Topics:

These are intensive workshops that instruct participants on how to design experiments, and efficiently manage & analyze data. They focus on the workflow for a specific type of next-generation sequencing application (i.e RNA-seq, ChIP-seq). These workshops require participants to have taken one or more of the Basic Data Skills workshops as listed in the table below.

Topic and Link(s) to lessons Prerequisites
Introduction to (bulk) RNA-seq using High-Performance Computing Introduction to shell
Introduction to Differential Gene Expression Analysis Introduction to R
Introduction to ChIP-seq Analysis Introduction to R & shell
Introduction to single cell RNA-seq Analysis Introduction to R

Current topics in bioinformatics series:

These workshops provide instruction on basic data skills as well as introduce new topics of interest to the community.

R-based short workshops:

Topic and Link(s) to lessons Prerequisites
Introduction to R None
Visualization in R Beginner R or Intro to R workshop
Introduction to R Practical Beginner R or Completion of the Intro to R online resource
Gene annotations and functional analysis of gene lists Beginner R or Intro to R workshop
Generating research analysis reports with RMarkdown Beginner R or Intro to R workshop
Interactive Data Visualization with Shiny in R (with Ista Zahn from the Harvard Business School) Beginner R or Intro to R workshop
Publication Perfect: Part I Beginner R or Completion of the Intro to R online resource
Publication Perfect: Part II Publication Perfect: Part I
Functional analysis of gene lists Beginner R or Intro to R workshop

Shell-based short workshops:

Topic and Link(s) to lessons Prerequisites
Introduction to the command-line interface None
Intermediate bash Beginner shell or Intro to the command-line interface
Version control using Git and Github Beginner shell or Intro to the command-line interface
Accessing genomic reference and experimental sequencing data Beginner shell or Intro to the command-line interface
Exploring genomic variants using GEMINI Beginner shell or Intro to the command-line interface

Other short workshops:

Topic and Link(s) to lessons Prerequisites
Introduction to Python None
Planning a bulk RNA-seq analysis: Part I None
Planning a bulk RNA-seq analysis: Part II None
Make your (RNA-seq) data analysis reproducible- Taught by Julie Goldman from Countway Library None
Improving your (RNA-seq) data analysis using version control (Git) None

Contact us:

Email: hbctraining@hsph.harvard.edu

Webpage: http://bioinformatics.sph.harvard.edu/training/

Twitter: @bioinfocore