To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("QuasR")
In most cases, you don't need to download the package archive at all.
QuasR
Quantify and Annotate Short Reads in R
Bioconductor version: 3.0
This package provides a framework for the quantification and analysis of Short Reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest.
Author: Anita Lerch, Dimos Gaiditzis and Michael Stadler
Maintainer: Michael Stadler <michael.stadler at fmi.ch>
Citation (from within R,
enter citation("QuasR")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("QuasR")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("QuasR")
| R Script | An introduction to QuasR | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | ChIPSeq, Genetics, MethylSeq, Preprocessing, RNASeq, Sequencing, Software |
| Version | 1.6.2 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | GPL-2 |
| Depends | parallel, GenomicRanges(>= 1.13.3), Rbowtie |
| Imports | methods, zlibbioc, BiocGenerics, S4Vectors, IRanges, BiocInstaller, Biobase, Biostrings, GenomicRanges, BSgenome, Rsamtools(>= 1.13.1), GenomicFeatures(>= 1.17.13), ShortRead(>= 1.19.1), GenomicAlignments |
| LinkingTo | Rsamtools |
| Suggests | Rsamtools, rtracklayer, Gviz, RUnit, BiocStyle |
| 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 | QuasR_1.6.2.tar.gz |
| Windows Binary | QuasR_1.6.2.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | QuasR_1.6.2.tgz |
| Mac OS X 10.9 (Mavericks) | QuasR_1.6.2.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
Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!
Contact us: support.bioconductor.org
Hosting provided by Fred Hutchinson Cancer Research Center
Copyright © 2003 - 2015, Bioconductor
