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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("bioassayR")
In most cases, you don't need to download the package archive at all.
bioassayR
R library for Bioactivity analysis
Bioconductor version: 3.0
bioassayR provides tools for statistical analysis of small molecule bioactivity data
Author: Tyler Backman, Ronly Schlenk, Thomas Girke
Maintainer: Tyler Backman <tyler.backman at ucr.edu>
Citation (from within R,
enter citation("bioassayR")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("bioassayR")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("bioassayR")
| R Script | bioassayR Tutorial | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Bioinformatics, CellBasedAssays, DataImport, Infrastructure, MicrotitrePlateAssay, Proteomics, Software, Visualization |
| Version | 1.4.3 |
| In Bioconductor since | BioC 2.13 (R-3.0) |
| License | Artistic-2.0 |
| Depends | R (>= 3.1.0), DBI (>= 0.3.1), RSQLite (>= 1.0.0), methods, Matrix, rjson |
| Imports | XML |
| LinkingTo | |
| Suggests | BiocStyle, RCurl, ape, ChemmineR |
| 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 | bioassayR_1.4.3.tar.gz |
| Windows Binary | bioassayR_1.4.3.zip |
| Mac OS X 10.6 (Snow Leopard) | bioassayR_1.4.3.tgz |
| Mac OS X 10.9 (Mavericks) | bioassayR_1.4.3.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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