Bioinformatics and Statistics for Large-Scale Data

Shenzhen, China

2013-11-17 ~ 2013-11-22

Instructors

• Wolfgang Huber
• Simon Anders
• Gabriella Rustici
• Martin Morgan
• Xin Liu
• Gang Chen

Description

This international advanced course will provide training on bioinformatics and statistics methods for genomic research. It will give insight into how biological knowledge can be generated from high-throughput sequencing (DNA-Seq, RNA-seq, ChIP-seq) experiments and will illustrate how to analyze such data. The course covers both the underlying statistical and algorithmic concepts, and the practice of how to automate and code such analyses using the scripting language R. The course will be a mix of lectures and hands-on training. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of data under the guidance of the lecturers and teaching assistants. The EMBO Practical course will also teach the basics of the R/Bioconductor environment for statistical-bioinformatic data analysis. The course is aimed at PhD students, postdocs and interested faculty. The teaching language will be English. Basic experience in computer programming (writing scripts) is required.

Materials

Course package (Morgan) EMBOBGI_0.0.2.tar.gz Download and install as follows in R-3.0, starting R in the directory where you downloaded the file:

biocLite(c("ggplot2", "Biostrings", "ShortRead"))
install.packages("EMBOBGI_0.0.2.tar.gz", repos=NULL, type="source")

Day 2

• NGS Challenges (Rustici) pdf
• R Basics (Huber) pdf R script
• R / Bioconductor Introduction (Morgan) pdf
• Working with Sequence Data in R / Bioconductor – Exercises (Morgan) pdf, R script

Day 3

• Annotation (Morgan) pdf, R script
• RNA-seq Differential Expression Lab (Huber / Anders) pdf, R script, localUcscTable.csv

Day 4

• RNA-seq Differential Expression (Huber) pdf
• Multiple testing (Huber) pdf
• RNA-seq Differential Expression / Exon Use (Anders) pdf
• Ranges (Morgan) pdf, R-script
• Annotation and Ranges – Exercises (Morgan) pdf, R-script

Day 5

• Gene Set Enrichment (Morgan) pdf
• Archiving NGS data (Rustici) pdf
• Ensembl Coursebook (Rustici) pdf
• Pathway Analysis (Rustici) pdf
• Reactome (Rustici) pdf
• Mapping (Liu) pdf
• Variation Detection (Liu) pdf; drill pdf

Day 6

• Visualization (Huber) pdf
• Reproducible Research (Morgan) pdf work flow
• Machine Learning (Chen) zip