Informatics for RNA-Seq Analysis 2019

Do these before coming to the workshop:

1) R Preparation tutorials: You are expected to be familiar with R before the workshop. If you are unfamiliar with R, here are some suggested tutorials:

• The CBW R tutorial or R Tutorial
• The R command cheat sheet
• R Plotting Reference

2) UNIX Preparation tutorials: You are expected to be familiar with basic command line usage before the workshop. If you are unfamiliar with the command line, here are some suggested tutorials:

• UNIX Bootcamp
• UNIX Bootcamp alternative
• Unix Cheat sheet

3) Sequencing Terminology

Read these before coming to the workshop:

• Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud

• Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration

• Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown

• ENCODE RNA-Seq Standards

• Methods to study splicing from high-throughput RNA sequencing data

• A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

• De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

Optional readings:

• HISAT: a fast spliced aligner with low memory requirements

• StringTie enables improved reconstruction of a transcriptome from RNA-seq reads

• Ballgown bridges the gap between transcriptome assembly and expression analysis

• HTSeq–a Python framework to work with high-throughput sequencing data

• edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

• Full-length transcriptome assembly from RNA-Seq data without a reference genome