BioC 2010

Seattle, WA

2010-07-29 ~ 2010-07-30

Instructors

• David Fredricks
• Stephen Friend
• Jay Shendure
• Atul Butte
• Simon Tavare
• Paul Flicek
• Lior Pachter
• Simon Anders
• Patrick Aboyoun
• Vincent Carey
• Marc Carlson
• Steffen Durinck
• Greg Finak
• Nishant Gopalakrishnan
• Wolfgang Huber
• Michael Lawrence
• James MacDonald
• Davis McCarthy
• Martin Morgan
• Herve Pages
• Mark Robinson
• Chao-Jen Wong
• Julie Zhu

Description

This conference highlights current developments within and beyond Bioconductor, an international open source and open development software project for the analysis and comprehension of high-throughput genomic data.

Materials

Morning Talks

• The Human Microbiome - David Fredricks, Fred Hutchinson Cancer Research Center.
• Better Maps of Disease: Building a commons for evolving generative models of disease - Stephen Friend, SAGE Bionetworks.
• Next Generation Mendelian Genetics by Exome Sequencing - Jay Shendure, University of Washington.
• Exploring Genomic Medicine Through Integrative Bioinformatics - Atul Butte, Stanford Center for Biomedical Informatics Research.
• Sparse partitioning: a tool for analyzing regression problems with many tertiary predictors - Simon Tavare, University of Southern California.
• Generation gap: How existing bioinformatics resources are adapting to high-throughput sequencing - Paul Flicek, European Bioinformatics Institute.
• Statistical Challenges in transcriptome sequencing - Lior Pachter, University of California, Berkeley.
• Differential expression analysis for sequencing count data - Simon Anders, European Bioinformatics Institute.

Afternoon Labs

Introduction to R

Instructor: Chao-Jen Wong

• Introduction to R
• First Steps with R
• Getting Started with Lattice

Install command:

source("http://bioconductor.org/course-packages/install-HTSTrack.R")

Efficient R Programming

Instructor: Martin Morgan

• Efficient R Programming
• Efficient R Programming Exercises

Install command:

source("http://bioconductor.org/course-packages/install-EfficientR.R")

Using limma for differential expression

Instructor: James W. MacDonald

• Using limma for differential expression

Data mining with biomaRt

Instructor: Steffen Durinck

• Database mining with biomaRt

ChIPpeakAnno Practical

Instructor: Lihua Julie Zhu

• ChIPpeakAnno Practical

Transcript centric annotations and high-throughput sequencing

Instructors: Marc Carlson / Herve Pages

• Using the GenomicFeatures package
• Genomic Features and Sequences in Bioconductor

Install command:

source("http://bioconductor.org/course-packages/install-HTSTrack.R")

Bioconductor tools for input and quality assessment of high-throughput sequence data

Instructors: Patrick Aboyoun / Martin Morgan

• Four exercises using Bioconductor Sequence Infrastructure
• Exercises: Reading and Manipulating Short Reads
• Exercises: An Introduction to Rsamtools
• Exercises: A Simple ChIP-Seq Workflow
• Exercises: A Simple RNA-seq Use Case

Install command:

source("http://bioconductor.org/course-packages/install-HTSTrack.R")

Analyzing and Visualizing ChIP-seq Data

Instructor: Michael Lawrence

• Some Basic Analysis of ChIP-Seq Data

Analysis of genome-scale count data in Bioconductor

Instructors: Mark Robinson / Davis McCarthy

• Analysis of genome-scale count data in Bioconductor
• Robinson_McCarthy_BioC2010.zip

Using image data for statistical analysis and modeling

Instructor: Wolfgang Huber

• Using image data for statistical analysis and modeling (slides)
• Using image data for statistical analysis and modeling (R script)
• Image of actin in cells
• Image of DNA in cells
• Image of tubulin in cells

Genetics of gene expression: comprehensive eQTL search

Instructor: Vince Carey

• Genetics of gene expression (lab)
• Genetics of gene expression (R script)

Gene centric annotations

Instructor: Marc Carlson

• Using Annotations in Bioconductor

Install command:

source("http://bioconductor.org/course-packages/install-HTSTrack.R")

Analyzing flow cytometry data in Bioconductor

Instructors: Nishant Gopalakrishnan / Chao-Jen Wong

• Brief Intro to R for Flow Packages Users
• Analyzing flow cytometry data in Bioconductor
• Flow cytometry analysis Lab
• Flow cytometry analysis Lab Solutions

Install command:

source("http://bioconductor.org/course-packages/install-flowTrack.R")

Automated Gating and Metaclustering of High Content Flow Cytometry Data

Instructor: Greg Finak

• Automated Gating and Metaclustering for Flow Cytometry Data
• Automated Gating and Metaclustering for Flow Cytometry Data (white paper)

Install command:

source("http://bioconductor.org/course-packages/install-flowTrack.R")