Last data update: 2014.03.03
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clippda
Package: clippda
Title: A package for the clinical proteomic profiling data analysis
Version: 1.22.0
Date: 2011/09/16
Author: Stephen Nyangoma
Description: 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.
Depends: R (>= 2.13.1), limma, statmod, rgl, lattice, scatterplot3d,
graphics, grDevices, stats, utils, Biobase, tools, methods
Maintainer: Stephen Nyangoma <s.o.nyangoma@bham.ac.uk>
License: GPL (>=2)
Collate: checkNo.replicates.R sampleClusteredData.R
sampleSize3DscatterPlots.R sampleSizeContourPlots.R
mostSimilarTwo.R negativeIntensitiesCorrection.R
phenoDataFrame.R preProcRepeatedPeakData.R spectrumFilter.R f.R
ztwo.R ZvaluescasesVcontrolsPlots.R ZvaluesfrommultinomPlots.R
betweensampleVariance.Generic.R fisherInformation.Generic.R
proteomicsExprsData.Generic.R proteomicspData.Generic.R
replicateCorrelations.Generic.R sampleSizeGeneric.R
sampleSizeParameters.Generic.R
sample_technicalVaraiance.Generic.R
aclinicalProteomicData.class.R aclinicalProteomicData.methods.R
betweensampleVariance.Method.R fisherInformation.Method.R
proteomicsExprsData.Method.R proteomicspData.Method.R
replicateCorrelations.Method.R sampleSizeMethod.R
sampleSizeParameters.Method.R sample_technicalVariance.Method.R
LazyLoad: yes
ZipData: yes
URL: http://www.cancerstudies.bham.ac.uk/crctu/CLIPPDA.shtml
Packaged: 2016-05-04 03:18:38 UTC; biocbuild
biocViews: Proteomics, OneChannel, Preprocessing,
DifferentialExpression, MultipleComparison
NeedsCompilation: no
● BiocViews: DifferentialExpression, MultipleComparison, OneChannel, Preprocessing, Proteomics
●
1 images,
36 functions,
1 datasets
●
Reverse Depends: 0
Install log
* installing to library '/home/ddbj/local/lib64/R/library'
* installing *source* package 'clippda' ...
** R
** data
** inst
** preparing package for lazy loading
** help
*** installing help indices
converting help for package 'clippda'
finding HTML links ... done
ZvaluescasesVcontrolsPlots html
ZvaluesfrommultinomPlots html
aclinicalProteomicsData-class html
aclinicalProteomicsData-methods html
betweensampleVariance-methods html
betweensampleVariance html
checkNo.replicates html
clippda-package html
f html
fisherInformation-methods html
fisherInformation html
liverRawData html
liver_pheno html
liverdata html
mostSimilarTwo html
negativeIntensitiesCorrection html
phenoDataFrame html
pheno_urine html
preProcRepeatedPeakData html
proteomicsExprsData-methods html
proteomicsExprsData html
proteomicspData-methods html
proteomicspData html
replicateCorrelations-methods html
replicateCorrelations html
sampleClusteredData html
sampleSize-methods html
sampleSize html
sampleSize3DscatterPlots html
sampleSizeContourPlots html
sampleSizeParameters-methods html
sampleSizeParameters html
sample_technicalVariance-methods html
sample_technicalVariance html
show-methods html
spectrumFilter html
ztwo html
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (clippda)
Making 'packages.html' ... done
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