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tweeDEseq
RNA-seq data analysis using the Poisson-Tweedie family of distributions
Bioconductor version: 3.0
Differential expression analysis of RNA-seq using the Poisson-Tweedie family of distributions.
Author: Juan R Gonzalez <jrgonzalez at creal.cat> and Mikel Esnaola <mesnaola at creal.cat> (with contributions from Robert Castelo <robert.castelo at upf.edu>)
Maintainer: Juan R Gonzalez <jrgonzalez at creal.cat>
Citation (from within R,
enter citation("tweeDEseq")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("tweeDEseq")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("tweeDEseq")
| R Script | tweeDEseq: analysis of RNA-seq data using the Poisson-Tweedie family of distributions | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, RNASeq, Sequencing, Software, StatisticalMethod |
| Version | 1.12.0 |
| In Bioconductor since | BioC 2.9 (R-2.14) |
| License | GPL (>= 2) |
| Depends | R (>= 2.12.0) |
| Imports | MASS, limma, edgeR, parallel, cqn |
| LinkingTo | |
| Suggests | tweeDEseqCountData, xtable |
| SystemRequirements | |
| Enhances | |
| URL | http://www.creal.cat/jrgonzalez/software.htm |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | tweeDEseq_1.12.0.tar.gz |
| Windows Binary | tweeDEseq_1.12.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | tweeDEseq_1.12.0.tgz |
| Mac OS X 10.9 (Mavericks) | tweeDEseq_1.12.0.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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