Bioinformatics for Cancer Genomics 2019

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Pre-workshop Tutorials

It is in your best interest to complete these before the workshop.

1) R Preparation tutorials: You are expected to have completed the following tutorials in R beforehand. The tutorial should be very accessible even if you have never used R before.

• The CBW R tutorial
• Quick and Dirty Guide to R
• The R Tutorial up to and including 5. Basic Plots
• The R command cheat sheet
• The R 4 Data Science tutorial, to the end of the Explore section at a minimum.
• The ggplot2 cheat sheet

2) UNIX Preparation tutorials:

• UNIX Bootcamp
• Tutorials #1-3 on UNIX Tutorial for Beginners
• Unix Cheat sheet

3) Sequencing Terminology

4) Cytoscape Preparation tutorials: Complete the introductory tutorial to Cytoscape

• Introduction to Cytoscape3 - User Interface

• Introduction to Cytoscape3 - Welcome Screen

• Filtering and Editing in Cytoscape 3

Pre-workshop Readings

Before coming to the workshop, read these:

• Database resources of the National Center for Biotechnology Information

• COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer

• Cancer genome sequencing study design

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

• Genome structural variation discovery and genotyping

• A survey of sequence alignment algorithms for next-generation sequencing

• Genotype and SNP calling from next-generation sequencing data

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

• 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

• Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap

• The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function

• GeneMANIA Prediction Server 2013 Update

• How to visually interpret biological data using networks

• g:Profiler–a web-based toolset for functional profiling of gene lists from large-scale experiments

• g:Profiler–a web server for functional interpretation of gene lists (2011 update)

• Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles

• Expression data analysis with Reactome

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