To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("ggtut")
In most cases, you don't need to download the package archive at all.
ggtut
support for tutorial on genetics of gene expression ISMB 2011
Bioconductor version: 3.0
various resources for genetics of expression with R/bioc
Author: VJ Carey <stvjc at channing.harvard.edu>
Maintainer: VJ Carey <stvjc at channing.harvard.edu>
Citation (from within R,
enter citation("ggtut")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("ggtut")
Documentation
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | ExperimentData |
| Version | 0.3.2 |
| License | Artistic-2.0 |
| Depends | R (>= 2.14.0), GGtools(>= 3.11.32), ff, GenomicRanges, snpStats, GGdata, GenomicFeatures, ChIPpeakAnno, Rsamtools(>= 1.5.35), cheung2010, SNPlocs.Hsapiens.dbSNP.20120608, hmyriB36 |
| Imports | |
| LinkingTo | |
| Suggests | rtracklayer, GenomicFeatures, ChIPpeakAnno, TxDb.Hsapiens.UCSC.hg18.knownGene |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | ggtut_0.3.2.tar.gz |
| Windows Binary | ggtut_0.3.2.zip |
| Mac OS X 10.6 (Snow Leopard) | ggtut_0.3.2.tgz |
| Mac OS X 10.9 (Mavericks) | ggtut_0.3.2.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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