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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("metahdep")
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metahdep
Hierarchical Dependence in Meta-Analysis
Bioconductor version: 3.0
Tools for meta-analysis in the presence of hierarchical (and/or sampling) dependence, including with gene expression studies
Author: John R. Stevens, Gabriel Nicholas
Maintainer: John R. Stevens <john.r.stevens at usu.edu>
Citation (from within R,
enter citation("metahdep")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("metahdep")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("metahdep")
| R Script | metahdep Primer | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, Microarray, Software |
| Version | 1.24.0 |
| In Bioconductor since | BioC 2.4 (R-2.9) |
| License | GPL-3 |
| Depends | R (>= 2.10), methods |
| Imports | |
| LinkingTo | |
| Suggests | affyPLM |
| 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 | metahdep_1.24.0.tar.gz |
| Windows Binary | metahdep_1.24.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | metahdep_1.24.0.tgz |
| Mac OS X 10.9 (Mavericks) | metahdep_1.24.0.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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