To install this package, start R and enter:
## try http if https is not available source("https://bioconductor.org/biocLite.R") biocLite("EBSeqHMM")
In most cases, you don't need to download the package archive at all.
Bioconductor version: 3.1
The EBSeqHMM package implements an auto-regressive hidden Markov model for statistical analysis in ordered RNA-seq experiments (e.g. time course or spatial course data). The EBSeqHMM package provides functions to identify genes and isoforms that have non-constant expression profile over the time points/positions, and cluster them into expression paths.
Author: Ning Leng, Christina Kendziorski
Maintainer: Ning Leng <nleng at wisc.edu>
Citation (from within R,
enter citation("EBSeqHMM")
):
To install this package, start R and enter:
## try http if https is not available source("https://bioconductor.org/biocLite.R") biocLite("EBSeqHMM")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("EBSeqHMM")
R Script | HMM | |
Reference Manual | ||
Text | NEWS |
biocViews | Bayesian, DifferentialExpression, GeneExpression, HiddenMarkovModel, MultipleComparison, RNASeq, Sequencing, Software, StatisticalMethod, TimeCourse |
Version | 1.2.0 |
In Bioconductor since | BioC 3.0 (R-3.1) (1 year) |
License | Artistic-2.0 |
Depends | EBSeq |
Imports | |
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URL | |
Depends On Me | |
Imports Me | |
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Build Report |
Follow Installation instructions to use this package in your R session.
Package Source | EBSeqHMM_1.2.0.tar.gz |
Windows Binary | EBSeqHMM_1.2.0.zip |
Mac OS X 10.6 (Snow Leopard) | EBSeqHMM_1.2.0.tgz |
Mac OS X 10.9 (Mavericks) | EBSeqHMM_1.2.0.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/EBSeqHMM/tree/release-3.1 |
Package Short Url | http://bioconductor.org/packages/EBSeqHMM/ |
Package Downloads Report | Download Stats |
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