To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("SSPA")
In most cases, you don't need to download the package archive at all.
SSPA
General Sample Size and Power Analysis for Microarray and Next-Generation Sequencing Data
Bioconductor version: 3.0
General Sample size and power analysis for microarray and next-generation sequencing data.
Author: Maarten van Iterson
Maintainer: Maarten van Iterson <mviterson at gmail.com>
Citation (from within R,
enter citation("SSPA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("SSPA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SSPA")
| R Script | SSPA Overview | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | GeneExpression, Microarray, RNASeq, Software, StatisticalMethod |
| Version | 2.6.0 |
| In Bioconductor since | BioC 2.4 (R-2.9) |
| License | GPL (>= 2) |
| Depends | R (>= 2.12), methods, qvalue, lattice, limma |
| Imports | graphics, stats |
| LinkingTo | |
| Suggests | BiocStyle, genefilter, edgeR, DESeq |
| SystemRequirements | |
| Enhances | |
| URL | http://www.humgen.nl/MicroarrayAnalysisGroup.html |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | SSPA_2.6.0.tar.gz |
| Windows Binary | SSPA_2.6.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | SSPA_2.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | SSPA_2.6.0.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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