To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("Rnits")
In most cases, you don't need to download the package archive at all.
Rnits
R Normalization and Inference of Time Series data
Bioconductor version: 3.0
R/Bioconductor package for normalization, curve registration and inference in time course gene expression data
Author: Dipen P. Sangurdekar <dipen.sangurdekar at gmail.com>
Maintainer: Dipen P. Sangurdekar <dipen.sangurdekar at gmail.com>
Citation (from within R,
enter citation("Rnits")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("Rnits")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("Rnits")
| R Script | R/Bioconductor package for normalization and differential expression inference in time series gene expression microarray data. | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DifferentialExpression, GeneExpression, Microarray, Normalization, Software, TimeCourse |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL-3 |
| Depends | R (>= 3.1.0), Biobase, ggplot2, limma, methods |
| Imports | affy, boot, impute, splines, graphics, qvalue, reshape2 |
| LinkingTo | |
| Suggests | BiocStyle, knitr, GEOquery, stringr |
| 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 | Rnits_1.0.0.tar.gz |
| Windows Binary | Rnits_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | Rnits_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | Rnits_1.0.0.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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