Function reference • dsOmicsClient

All functions
`checkForExpressionSet()`	Check if object exists on the study server and if it's an ExpressionSet
`.eafPlot()`	Auxiliary function for `eafPlot`
`.pzPlotgg()`	Auxiliary function for `pzPlot`
`ds.addPhenoData2eSet()`	Add Phenotype data to ExpressionSet
`ds.alleleFrequency()`	Allelic frequency
`ds.createRSE()`	Create a RangedSummarizedExperiment from a RNAseq count table and a phenotypes table
`ds.DESeq2()`	Server-side Differential Gene Expression analysis using DESeq2
`ds.edgeR()`	Server-side Differential Expression Analysis using edgeR
`ds.exactHWE()`	Hardy-Weinberg Equilibrium testing
`ds.fastGWAS()`	Fast genome-wide association analysis (GWAS)
`ds.featureData()`	Retrieve information on features from eSets and RSEs.
`ds.featureNames()`	Retrieve feature names from eSets and RSEs.
`ds.fvarLabels()`	Retrieve phenotypic data (e.g. covariates) from eSets and RSEs.
`ds.genoDimensions()`	Get main dimensions of Genotype data
`ds.GenotypeData()`	Creates a GenotypeData object at each server
`ds.getChromosomeNames()`	Get names of chromosomes
`ds.getSNPs()`	Retrieve SNPs from
`ds.getSNPSbyGen()`	Subset GDS with gene(s)
`ds.glmSNP()`	Logistic regression analysis of pooled data for each SNP site in study
`ds.index.gdsn()`	Retrieve phenotypic data (e.g. covariates) from eSets.
`ds.limma()`	Server-side Differential Gene Expression analysis using limma
`ds.lmFeature()`	Linear regression analysis of pooled data for each CpG site in study
`ds.make_valid_names()`	Rename column names and character variables
`ds.metaGWAS()`	Genome-wide association analysis (GWAS)
`ds.nFeatures()`	Retrieve the number of features for eSets and RSEs.
`ds.nSamples()`	Retrieve the number of samples for eSets and RSEs.
`ds.PCA()`	Principal Component Analysis (PCA) on SNP genotype data
`ds.PCASNPS()`	Principal Component Analysis (PCA) on SNP genotype data
`ds.PLINK()`	Genome-wide association analysis (GWAS) using PLINK
`ds.PRS()`	Get Ploygenic Risk Score
`ds.removeOutliers()`	Filter potential CpG outliers
`ds.RNAseqPreproc()`	Filter Genes By Expression Level
`ds.snptest()`	Interface to run SNPtest commands on a ssh connection (with SNPtest 2.5.2 installed)
`ds.subsetExpressionSet()`	Subset ExpressionSet
`ds.table_gds()`	Contingency tables of phenotypes
`ds.varLabels()`	Retrieve phenotypic data (e.g. covariates) from eSets.
`eafPlot()`	EAF plot
`get_EGA_url()`	Get EGA URL
`get_ga4gh_url()`	Get GA4GH URL
`glmSNP()`	Fits a GLM to assess association between the outcome (binary variable) and a given SNP
`lambdaNPlot()`	Lambda-N plot
`lmFeature()`	Fits a LM to assess association between the features (outcome) and grouping variable (e.g case/control, condition, ...)
`LocusZoom()`	LocusZoom
`manhattan()`	Mannhattan Plot
`metaBetaValues()`	Meta-analysis of beta values
`metaPvalues()`	Meta-analysis of p-values
`plot(<dsLmFeature>)`	Generate a QQ-plot of p-values output from any omic data analysis
`plotPCA()`	Plot the results of a `ds.PCA()`
`plotPCASNPS()`	Plot the results of a `ds.PCASNPS()`
`pzPlot()`	P-Z plot
`qqplot()`	Create a quantile-quantile plot with ggplot2.
`seNPlot()`	SE-N Plot
`standardizeGenoData()`	Get standaridization coefficients of Genotype data
`tolist()`	PLINK arguments in the DataSHIELD required format

Reference

All functions