- Home
- Bioconductor 2.14
- Software Packages
- clippda
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("clippda")
In most cases, you don't need to download the package archive at all.
clippda
A package for the clinical proteomic profiling data analysis
Bioconductor version: 2.14
Methods for the nalysis of data from clinical proteomic profiling studies. The focus is on the studies of human subjects, which are often observational case-control by design and have technical replicates. A method for sample size determination for planning these studies is proposed. It incorporates routines for adjusting for the expected heterogeneities and imbalances in the data and the within-sample replicate correlations.
Author: Stephen Nyangoma
Maintainer: Stephen Nyangoma <s.o.nyangoma at bham.ac.uk>
Citation (from within R,
enter citation("clippda")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("clippda")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("clippda")
| R Script | Sample Size Calculation | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, MultipleComparison, OneChannel, Preprocessing, Proteomics, SampleSize, Software |
| Version | 1.14.0 |
| In Bioconductor since | BioC 2.5 (R-2.10) |
| License | GPL (>=2) |
| Depends | R (>= 2.13.1), limma, statmod, rgl, lattice, scatterplot3d, graphics, grDevices, stats, utils, Biobase, tools, methods |
| Imports | |
| Suggests | |
| System Requirements | |
| URL | http://www.cancerstudies.bham.ac.uk/crctu/CLIPPDA.shtml |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | clippda_1.14.0.tar.gz |
| Windows Binary | clippda_1.14.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | clippda_1.14.0.tgz |
| Mac OS X 10.9 (Mavericks) | clippda_1.14.0.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
Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!
Contact us: support.bioconductor.org
Hosting provided by Fred Hutchinson Cancer Research Center
Copyright © 2003 - 2014
