Man pages for llrs/integration-helper
Facilitate the integration

access_reactomeReturn data from reactome
allCombLogical vectors of meta data
analyzeAnalyze a sgcca object
angleCalculates the angle between to slopes
avesMethod to simplify AVE
biological_relationshipsPerforms the calculation of biological information
boot_evaluateEvaluates the boostrapping of RGCCA
boots_corrBootstrapping to asses how probable is to have such...
boot_sgccaBootstrap sgcca
cca_rgccaCalculate correlation and covariance between CCA dimensions
check_designValidate designs
circleA circle of radium 2
circleFunCreate a circle
clean_unvariableRemove unvariable features
colorsUseful colors
comb_prevalenceLook for prevalene in combinations of two
compAnalyze the data for the relationship in time
compareCompares two objects of class sgcca
compare.correlationsCalculates the z-score of two correlations
contingency_taxaCompares the taxonomy of the otus
convert.z.scoreZ-score to p-value
correctCheck that the network is fully connected
cor_signSignificative correlation
cors_rgccaCheck the efficacy of RGCCA
dist2dCalculate the distance between a line and a point
ensembl2symbolTranslate ensmbl to symbols
epitheliumEFunction to read the epithelium signature
fastercheckCheck if a vector is in the matrix
filter_RNAseqFilter expressions
filter_valuesFilter correlations
getAVEsRetrieve inner AVE
improve.sgccaImprove the information on sgcca classes
Integration-packageIntegrates data
kFoldingIndexes for K-folds
loo_functionsFunction to export a function
looIndexIndexes without one sample
makeRectsMake a rectangle at those cells
McKeonHomeogenityCalculates McKeon Homeogenity
meta_i_normNormalize 16S biopsies metadata
meta_r_normNormalize the metadata of the RNA
meta_s_normNormalize 16S stools metadata
model_columnsAdapt data for a CCA
model_RGCCAPrepare data for CCA.
m_semSummarize a model
norm_expr_colnamesChange names of expression
norm_otusNormalize OTUS
norm_RNAseqNormalize RNAseq
pathsPerMicroEnrichment by microorganisms
plotAVEsDistribution of inner AVE
plot_corPlot a correlation with ggplot
plot_interestingPlot PCA of interesting variables
plot_samplesPlot samples
plot_single_corPlot correlations
plot_variablesPlot bullseye
prevalenceTest prevalence
prevalence_tabCalculates the presence or absence of a microorganism
probability_samplesCalculates the probability of obtaining these samples.
pvalueCalculates the p.value
ratioRatio of prevalence
readSGCCARead component
relevantList the correlations
select_genes_intFilter genes
select_varSelect important variables
selectVarSelect variable from bootstrapping
semStandard error of the mean
sign_corList the correlations
sizeNumber of samples
store_microStore result by microorganism
subsetDataSubset a list
subSymmSubsitute in a symmetric matrix
symmCreate symmetric matrix
taxonomyClean and prepare the data from IMNGS
tidyerClean the output of a sgcca object
tol21rainbowRainbow colors
trimVerTrim version number of genes
two.sidedTwo sided test
variablesExtract in a tidy way the information about the variables
variables_weightPlot density of the weight of components
weight_designCheck a design for different weights
weightsSelect the wegiths and adds information for human RNAseq
weights_bayesIndependence between genes and OTUs
weights_correlationCorrelation weights
weights_otusSelect the wegiths and adds information for taxa RNAseq
wilks_rgccaCheck the efficacy of RGCCA
write_corTranslate symbols and store
llrs/integration-helper documentation built on June 14, 2019, 7:06 p.m.