Difference between revisions of "TrainingBlocks"

The 14-hour hands on course on how to analyze RNA-seq data: data formats, quality control, mapping, differential expression, functional analysis. A small RNA-seq project was handed to the trainees who had one week to process it. It was then discussed during a final 4-hour session. The material is available as a [git page].

Two three-hour sessions to understand some of the main genomics data formats (fasta, fastq, gtf, bed...) and to learn how to parse them. Course material available here.

The eight three and a half-hour hands-on sessions of how to use R-Studio, learn and practice the basics in R, perform plotting and exploratory data analysis. Course material available here.

The two four-hour hands-on sessions of how to create and use containers (Docker and Singularity). Course material available here.

The four four-hour hands-on sessions of how to use R-Studio, learn and practice the basics in R, and perform basic plotting and data analysis. For more information, course materials, and links to external teaching resources, visit the course page.

The three two-hour hands-on sessions of how to use R-Studio and perform basic plotting and data analysis. For more information, course materials, and links to external teaching resources, visit the course page.

12h very slow paced hands-on to learn how to use R. For more information, course materials, and links to external teaching resources, visit the course website.

In this course, the introduction to R is offered in 4 slow-paced practicums for absolute beginners, followed by 3 fast-paced practicums of statistical modules. The statistics material is offered in 3 consecutive modules, each containing a morning lecture and an afternoon practicum in a computer class.
For more information, course materials, and links to external teaching resources, visit the course page.

The hands-on sessions of how to use R-Studio and perform basic plotting and data analysis. For more information, course materials, and links to external teaching resources, visit the course page.

This introductory course to Statistics and Probability theory was modeled after the university-level course Statistics 101.
For more information, course materials, and links to external teaching resources, visit the course website.

The courses on basic Linux and how to use the CRG cluster are regularly run by the CRG SIT Unit and can be found at the SIT website (accessible only from CRG network).