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scrime  

Analysis of High-Dimensional Categorical Data Such as SNP Data
View on CRAN: Click here


Download and install scrime package within the R console
Install from CRAN:
install.packages("scrime")

Install from Github:
library("remotes")
install_github("cran/scrime")

Install by package version:
library("remotes")
install_version("scrime", "1.3.5")



Attach the package and use:
library("scrime")
Maintained by
Holger Schwender
[Scholar Profile | Author Map]
First Published: 2008-01-16
Latest Update: 2018-12-01
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.
How to cite:
Holger Schwender (2008). scrime: Analysis of High-Dimensional Categorical Data Such as SNP Data. R package version 1.3.5, https://cran.r-project.org/web/packages/scrime. Accessed 20 Apr. 2025.
Previous versions and publish date:
1.0.0 (2008-01-16 10:15), 1.0.7 (2009-01-09 20:21), 1.1.2 (2009-01-27 17:41), 1.1.4 (2009-05-11 20:49), 1.1.6 (2009-05-19 21:09), 1.1.7 (2009-10-14 11:34), 1.1.9 (2009-11-01 17:17), 1.2.0 (2010-04-28 09:26), 1.2.1 (2010-07-29 11:14), 1.2.5 (2011-03-29 20:21), 1.2.6 (2011-06-09 08:04), 1.2.8 (2011-11-02 18:26), 1.2.9 (2012-10-03 12:21), 1.3.2 (2013-03-14 07:27), 1.3.3 (2013-09-02 00:22)
Other packages that cited scrime R package
View scrime citation profile
Other R packages that scrime depends, imports, suggests or enhances
Complete documentation for scrime
Functions, R codes and Examples using the scrime R package
Some associated functions: abf . analyse.models . buildSNPannotation . colEpistatic . computeContCells . computeContClass . fblr . gknn . identifyMonomorphism . knncatimpute . knncatimputeLarge . pamCat . pcc . predict.pamCat . predictFBLR . recodeAffySNP . recodeSNPs . rowCATTs . rowChisq2Class . rowChisqStats . rowCors . rowFreqs . rowHWEs . rowMAFs . rowMsquares . rowScales . rowTables . rowTrendFuzzy . rowTrendStats . scrime-internal . shortenGeneDescription . showChanges . simulateSNPcatResponse . simulateSNPglm . simulateSNPs . smc . snp2bin . summary.simSNPglm . 
Some associated R codes: abf.R . analyse.models.R . buildSNPannotation.R . buildSNPmat.R . canberra2Mats.R . check4Monomorphism.R . checkATCG.R . checkCatMat.R . checkDist.R . checkDistMat.R . checkMatSNP.R . checkTableList.R . checkX1X2.R . chisqClass2.R . chisqInd.R . cohen.R . cohen2Mats.R . colEpistatic.R . compChisqPval.R . compVarLevs.R . computeContCells.R . computeContClass.R . constructMatCheck.R . constructMatIA.R . dist2Mats.R . euclidean2Mats.R . evalRedundancy.R . fblr.R . fblr.weight.R . getBinDomRec.R . getBinGenotype.R . getCall.R . getDistance.R . getListIdentity.R . getMatFuzzy.R . getResponse.R . gknn.R . ia.samp.R . identifyMonomorphism.R . knncatimpute.R . knncatimputeLarge.R . manhattan2Mats.R . maximum2Mats.R . mc2Mats.R . minkowski2Mats.R . minrc.R . minrc2Mats.R . modeDist.R . pamCat.R . pcc.R . pcc2Mats.R . predict.pamCat.R . predictFBLR.R . print.pamCat.R . print.simSNPcatResponse.R . print.simSNPglm.R . print.simulatedSNPs.R . recodeAffySNP.R . recodeCount.R . recodeFirst.R . recodeNoHete.R . recodeSNPs.R . removeRedundancy.R . replaceNAs.R . row2col.R . rowCATTs.R . rowChisq2Class.R . rowChisqMultiClass.R . rowChisqStats.R . rowCors.R . rowFreqs.R . rowHWEs.R . rowMAFs.R . rowMsquares.R . rowScales.R . rowTables.R . rowTrendFuzzy.R . rowTrendStats.R . sample.snpmat.R . showChanges.R . simulateSNPcatResponse.R . simulateSNPglm.R . simulateSNPs.R . smc.R . smc2Mats.R . snp1norm2Mats.R . snp2bin.R . summary.simSNPglm.R . weightMode.R .  Full scrime package functions and examples
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