To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RTCA")
In most cases, you don't need to download the package archive at all.
RTCA
Open-source toolkit to analyse data from xCELLigence System (RTCA)
Bioconductor version: 2.14
Import, analyze and visualize data from Roche(R) xCELLigence RTCA systems. The package imports real-time cell electrical impedance data into R. As an alternative to commercial software shipped along the system, the Bioconductor package RTCA provides several unique transformation (normalization) strategies and various visualization tools.
Author: Jitao David Zhang
Maintainer: Jitao David Zhang <davidvonpku at gmail.com>
Citation (from within R,
enter citation("RTCA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RTCA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RTCA")
| R Script | Introduction to Data Analysis of the Roche xCELLigence System with RTCA Package | |
| R Script | RTCAtransformation: Discussion of transformation methods of RTCA data | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | CellBasedAssays, Infrastructure, Software, TimeCourse, Visualization |
| Version | 1.16.0 |
| In Bioconductor since | BioC 2.5 (R-2.10) |
| License | LGPL-3 |
| Depends | methods, stats, graphics, Biobase, RColorBrewer, gtools |
| Imports | |
| Suggests | xtable |
| System Requirements | |
| URL | http://code.google.com/p/xcelligence/ http://www.xcelligence.roche.com/ http://www.nextbiomotif.com/Home/scientific-programming |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | RTCA_1.16.0.tar.gz |
| Windows Binary | RTCA_1.16.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | RTCA_1.16.0.tgz |
| Mac OS X 10.9 (Mavericks) | RTCA_1.16.0.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
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