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clippda (version 1.22.0)

A package for the clinical proteomic profiling data analysis

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.

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Version

Version

1.22.0

License

GPL (>=2)

Maintainer

Stephen Nyangoma

Last Published

February 15th, 2017

Functions in clippda (1.22.0)

sampleSizeParameters-methods

~~ Methods for Function sampleSizeParameters
proteomicsExprsData

A generic fuction to extract duplicate SELDI data from an object of aclinicalProteomicsData class in the same format as the data from Biomarkers wizard
phenoDataFrame

A generic function to set classes for the variables in the dataframe of phenotypic information.
checkNo.replicates

A function to detect disparity in the number of replicates across assays
f

A function to compute adjustments for the effct of covariates (Z values) for an experiment with a binary exposure and a binary confounder
spectrumFilter

A function to filter out samples with conflicting pair-wise compound information
mostSimilarTwo

A function which indentifies two columns of a matrix, or dataframe, with the highest pairwise positive correlations
replicateCorrelations

A generic function to compute intraclass correlations
sampleSize3DscatterPlots

A function for 3D display of sample size in a multi parameter space
sampleSize-methods

~~ Methods for Function sampleSize
liver_pheno

A dataframe of phenotypic information
betweensampleVariance

A generic function for computing the biological variance and mean differences between cases and controls
sampleClusterdData

A function to arrange the data in sample-wise pairs
pheno_urine

A dataframe of phenotypic information
aclinicalProteomicsData-class

Class "aclinicalProteomicsData"
show-methods

Methods for Function show in Package `methods'
ZvaluesfrommultinomPlots

A generic functon to plot Density of Z values from a simulation from a multinomial population using the balanced and unbalanced studies and a 3D representaion of the Z values
proteomicspData-methods

Methods for Function proteomicspData
proteomicspData

A function to extract a dataframe of phenotypic information from an object of aclinicalProteomicsData class
liverdata

A dataframe of the protein expression data, peak information, and sample information
liverRawData

A dataframe of the protein expression data, peak information and sample information
fisherInformation-methods

Methods for Function fisherInformation
sampleSize

A function for sample size calculations
ZvaluescasesVcontrolsPlots

A function for ploting the odds of being a case vs control and their effects on adjustments for confounders
ztwo

A function to compute Z values when there are no covariates other than the cancer class
proteomicsExprsData-methods

Methods for Function proteomicsExprsData
clippda-package

A package for clinical proteomics profiling data analysis
preProcRepeatedPeakData

A function to pre-process repeated raw peak data
aclinicalProteomicsData-methods

S4 method for the aclinicalProteomicsData class
sampleSizeParameters

A generic function to calculate sample size parameters
negativeIntensitiesCorrection

A function to correct the data for the negative intensities caused by the normalization and background correction procedures of mass spectrometry data
sample_technicalVariance-methods

Methods for Function sample_technicalVariance
sampleSizeContourPlots

A function to construct a grid with contours for calculating sample size in multi dimensional parameter space
fisherInformation

A generic function to compute the heterogeneity correction factor in sample size calculations
betweensampleVariance-methods

Methods for Function betweensampleVariance
replicateCorrelations-methods

Methods for Function replicateCorrelations
sample_technicalVariance

A generic function for computing the technical variance