The Epigenomics Core has compiled detailed information about the different types of -seq experiments they're performing.
The course notes accompanying the Applied Bioinformatics Core's RNA-seq class contain a comprehensive introduction into many aspects of high-throughput sequencing data analysis.
An introduction into general ChIP-seq analysis can be found here, including a Glossary of HTS terms including the different file formats.
Online courses
- Applied Bioinformatics Core's Datacamp Course Introduction to R
- Applied Bioinformatics Core's Introduction to version control using RStudio
- Michael Love's Intro to Computational Biology
- Applied Bioinformatics Core's Datacamp Course Introduction to Git in RStudio
Articles
An excellent overview of the different sequencing techniques and applications: "Coming of age: ten years of next- generation sequencing technologies"
A good summary of sequencing platforms including publicly available data: "High-throughput sequencing"
A very good read (including the reviews and comments) that discusses many scientific as well as ethical issues surrounding batch effects in data generated by sequencing consortia: https://f1000research.com/articles/4-121/v1
Nature Methods has compiled a great selection of brief introductions into many statistical concepts that biologists should be familiar with, such as p-value calculations, replicate handling, visualizations etc.: Points of Significance Series
F1000Research has entire paper series ("gateways" or "channels") dedicated to specific topics, including data analyses using R: Channels