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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("inSilicoMerging")
In most cases, you don't need to download the package archive at all.
inSilicoMerging
Collection of Merging Techniques for Gene Expression Data
Bioconductor version: 3.0
Collection of techniques to remove inter-study bias when combining gene expression data originating from different studies.
Author: Jaro Vanderheijden [ctb], Quentin De Clerck [ctb], Jonatan Taminau [cre]
Maintainer: InSilico DB <support at insilicodb.com>
Citation (from within R,
enter citation("inSilicoMerging")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("inSilicoMerging")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("inSilicoMerging")
| R Script | Using the inSilicoMerging package | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Microarray, Software |
| Version | 1.10.1 |
| In Bioconductor since | BioC 2.10 (R-2.15) |
| License | GPL-2 |
| Depends | R (>= 2.11.1), Biobase |
| Imports | |
| LinkingTo | |
| Suggests | BiocGenerics, inSilicoDb |
| SystemRequirements | |
| Enhances | |
| URL | http://insilicodb.com/ |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | inSilicoMerging_1.10.1.tar.gz |
| Windows Binary | inSilicoMerging_1.10.1.zip |
| Mac OS X 10.6 (Snow Leopard) | inSilicoMerging_1.10.1.tgz |
| Mac OS X 10.9 (Mavericks) | inSilicoMerging_1.10.1.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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