To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MBASED")
In most cases, you don't need to download the package archive at all.
MBASED
Package containing functions for ASE analysis using Meta-analysis Based Allele-Specific Expression Detection
Bioconductor version: 3.0
The package implements MBASED algorithm for detecting allele-specific gene expression from RNA count data, where allele counts at individual loci (SNVs) are integrated into a gene-specific measure of ASE, and utilizes simulations to appropriately assess the statistical significance of observed ASE.
Author: Oleg Mayba, Houston Gilbert
Maintainer: Oleg Mayba <mayba.oleg at gene.com>
Citation (from within R,
enter citation("MBASED")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MBASED")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("MBASED")
| R Script | MBASED | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | GeneExpression, Sequencing, Software, Transcription |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | Artistic-2.0 |
| Depends | RUnit, BiocGenerics, BiocParallel, GenomicRanges |
| Imports | |
| LinkingTo | |
| Suggests | 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 | MBASED_1.0.0.tar.gz |
| Windows Binary | MBASED_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | MBASED_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | MBASED_1.0.0.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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