Data Science Training
The CCDL also offers training to teach researchers the data science skills to examine their own data. The training is focused on techniques for gene expression analysis.
People who attend the training sessions come will away with a basic understanding of:
R programming language and the bioconductor package ecosystem.
Processing bulk and single-cell RNA-seq data from raw all the way to downstream analyses.
Downstream analyses methods like differential expression analyses, hierarchical clustering, and preparing publication-ready plots.
Bay Area, CA
September 3-5 2019
Chan Zuckerberg Initiative Offices, Redwood City, CA
This training is fully booked!
We’re working on conducting more training sessions. Sign up and help us decide where to go next!
Our training materials are available freely on Github. We currently have four modules .
Intro to R and tidyverse
A brief introduction to using R programming language and the tidyverse package in context of gene expression data.
Learn how to process bulk RNA-seq data and apply commonly used analysis techniques like differential expression.
Learn how to process different types of scRNA-seq data and analyze them.
Learn to apply machine learning techniques like clustering to gene expression data.