Seattle, USA
2014-02-27 ~ 2014-02-28
Introduction to Bioconductor for Sequence Analysis introduces users with some R experience to Bioconductor, especially working with high-throughput sequence data. Day 1 develops core R and Bioconductor concepts for working with large and complicated data. Participants will become familiar with data classes, packages, and scripting and programming concepts that are important for common and integrated work flows in Bioconductor. Day 2 will put these skills to use for the analysis of RNAseq differential expression data, including initial quality assessment, pre-processing, differential representation, annotation, and visualization. The course involves a combination of presentations and hands-on exercises; participants should come prepared with a modern laptop with wireless internet access.
Download and install the package (containing all material) for use with R-3.1.0 / Bioconductor 2.14.
Install the course package with
source("http://bioconductor.org/biocLite.R")
dependencies <- c("Biostrings", "ShortRead", "ggplot2")
biocLite(dependencies)
install.packages("BiocIntro_0.0.3.tar.gz", repos=NULL)
Optionally, install suggested packages (used in exercises, etc) with
source("http://bioconductor.org/biocLite.R")
suggested <- c("BiocStyle", "knitr", "AnnotationHub",
"BSgenome.Hsapiens.UCSC.hg19", "BiocParallel", "Biostrings",
"GenomicAlignments", "GenomicFeatures", "GenomicRanges",
"Gviz", "IRanges", "PSICQUIC", "RNAseqData.HNRNPC.bam.chr14",
"TxDb.Hsapiens.UCSC.hg19.knownGene", "VariantAnnotation",
"biomaRt", "knitr", "org.Hs.eg.db", "parallel", "rtracklayer")
biocLite(suggested)
Explore the material through the following documents:
Introduction
Working with R
Sequencing work flows
Bioconductor for Sequence Analysis
RNA-Seq
Annotation and visualization
Packages »
Bioconductor's stable, semi-annual release:
Bioconductor is also available viaDocker Images and for use in the AnVIL.
Documentation »
Bioconductor
R / CRAN packages and documentation