2013-07-09 ~ 2013-07-09
DNA sequence analysis generates large volumes of data presenting challenging bioinformatic and statistical problems. This tutorial introduces Bioconductor packages and work flows for the analysis of sequence data. We learn about approaches for efficiently manipulating sequences and alignments, and introduce common work flows and the unique statistical challenges associated with RNA-seq, variant annotation, and other experiments. The emphasis is on exploratory analysis, and the analysis of designed experiments.The workshop emphasizes orientation within the Bioconductor milieu; we will touch on the Biostrings, ShortRead, GenomicRanges, edgeR, and VariantAnnotation, and other packages, with short exercises to illustrate the functionality of each package.
This package is already installed on your AMI. But you can install it on your own machine as follows:
Download the file above and install as follows in R-3.0, starting R in the directory where you downloaded the file:
biocLite(c("GenomicFeatures", "ShortRead", "VariantAnnotation", "edgeR", "bioDist", "DiffBind", "org.Dm.eg.db", "BSgenome.Dmelanogaster.UCSC.dm3", "TxDb.Dmelanogaster.UCSC.dm3.ensGene", "BSgenome.Hsapiens.UCSC.hg19", "TxDb.Hsapiens.UCSC.hg19.knownGene", "SNPlocs.Hsapiens.dbSNP.20101109", "MotifDb", "seqLogo", "ggplot2")) install.packages("useR2013_0.1.5.tar.gz", repos=NULL, type="source")
Bioconductor's stable, semi-annual release:
Common Bioconductor workflows include: