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scrime (version 1.2.9)

Analysis of High-Dimensional Categorical Data such as SNP Data

Description

Tools for the analysis of high-dimensional data developed/implemented at the group "Statistical Complexity Reduction In Molecular Epidemiology" (SCRIME). Main focus is on SNP data. But most of the functions can also be applied to other types of categorical data.

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Version

Install

install.packages('scrime')

Monthly Downloads

6,683

Version

1.2.9

License

GPL-2

Maintainer

Holger Schwender

Last Published

October 3rd, 2012

Functions in scrime (1.2.9)

predictFBLR

Predict Case Probabilities with Full Bayesian Logic Regression
recodeSNPs

Recoding of SNP Values
smc

Simple Matching Coefficient and Cohen's Kappa
simulateSNPs

Simulation of SNP data
summary.simSNPglm

Summarizing a simSNPglm object
identifyMonomorphism

Identification of Constant Variables
analyse.models

Summarize MCMC sample of Bayesian logic regression models
gknn

Generalized k Nearest Neighbors
shortenGeneDescription

Shorten the Gene Description
showChanges

Displaying Changes
rowMAFs

Rowwise Minor Allele Frequency
predict.pamCat

Predict Method for pamCat Objects
rowMsquares

Rowwise Linear Trend Test Based on Tables
rowFreqs

Rowwise Frequencies
colEpistatic

Cordell's Test for Epistatic Interactions
rowHWEs

Rowwise Test for Hardy-Weinberg Equilibrium
scrime-internal

Internal scrime functions
pcc

Pearson's Contingency Coefficient
rowScales

Rowwise Scaling
computeContClass

Rowwise Contigency Tables
computeContCells

Pairwise Contingency Tables
fblr

Full Bayesian Logic Regression for SNP Data
rowCors

Rowwise Correlation with a Vector
rowTrendFuzzy

Trend Test for Fuzzy Genotype Calls
simulateSNPglm

Simulation of SNP data
buildSNPannotation

Construct Annotation for Affymetrix SNP Chips
rowTrendStats

Rowwise Linear Trend Tests
knncatimpute

Missing Value Imputation with kNN
rowCATTs

Rowwise Cochran-Armitage Trend Test Based on Tables
knncatimputeLarge

Missing Value Imputation with kNN for High-Dimensional Data
snp2bin

Transformation of SNPs to Binary Variables
rowTables

Rowwise Tables
abf

Approximate Bayes Factor
pamCat

Prediction Analysis of Categorical Data
rowChisqStats

Rowwise Pearson's ChiSquare Statistic
simulateSNPcatResponse

Simulation of SNP Data with Categorical Response
rowChisq2Class

Rowwise Pearson's ChiSquare Test Based on Tables
recodeAffySNP

Recoding of Affymetrix SNP Values