Function reference

The `MirnaExperiment` class

Methods and accessors for objects of class MirnaExperiment, the main class in MIRit to work with miRNA and gene expression data.

mirnaDE(<MirnaExperiment>) geneDE(<MirnaExperiment>) significantMirnas(<MirnaExperiment>) significantGenes(<MirnaExperiment>) pairedSamples(<MirnaExperiment>) mirnaTargets(<MirnaExperiment>) integration(<MirnaExperiment>) show(<MirnaExperiment>): The 'MirnaExperiment' class

MirnaExperiment(): The constructor function for MirnaExperiment

pairedSamples(): View the relationship between miRNA and gene samples

Create example objects

Example datasets provided by MIRit for exploring the capabilities of the software.

mirnaCounts: Count matrix for microRNA expression in thyroid cancer

geneCounts: Count matrix for gene expression in thyroid cancer

loadExamples(): Load example MIRit objects

Differential expression analysis

The functions used to perform miRNA and gene differential expression analyses from start to finish.

plotDimensions(): Generate multidimensional scaling (MDS) plots to explore miRNA/gene expression distances

performMirnaDE() performGeneDE(): Perform differential expression analysis

addDifferentialExpression(): Manually add differential expression results to a MirnaExperiment object

mirnaDE() geneDE(): Extract differentially expressed miRNAs and genes from a MirnaExperiment object

significantMirnas() significantGenes(): Get the IDs of statistically differentially expressed miRNAs/genes

plotDE(): Represent differentially expressed miRNAs/genes as boxplots, barplots or violinplots

plotVolcano(): Produce volcano plots to display miRNA/gene differential expression

Functional enrichment

Methods and functions used to perform functional enrichment analysis of genes.

enrichmentResults(<FunctionalEnrichment>) enrichmentDatabase(<FunctionalEnrichment>) enrichmentMethod(<FunctionalEnrichment>) geneSet(<FunctionalEnrichment>) enrichmentMetric(<FunctionalEnrichment>) enrichedFeatures(<FunctionalEnrichment>) show(<FunctionalEnrichment>): The FunctionalEnrichment class

enrichGenes(): Perform functional enrichment analysis of genes

enrichTargets(): Perform an enrichment analysis of integrated microRNA targets

enrichedFeatures(): Extract the names of the pre-ranked features in a GSEA experiment

enrichmentBarplot(): Create a barplot for functional enrichment analysis

enrichmentDatabase(): Access the database used for functional enrichment analyses

enrichmentDotplot(): Create a dotplot for functional enrichment analysis

enrichmentMethod(): Access the method used for functional enrichment analyses

enrichmentMetric(): Extract the GSEA ranking metric used for functional enrichment analyses

enrichmentResults(): Access the results of functional enrichment analyses

geneSet(): Extract the gene-sets used for functional enrichment analyses

gseaPlot(): Create a GSEA plot that displays the running enrichment score (ES) for a given pathway

gseaRidgeplot(): Create a ridgeplot to display the results of GSEA analysis

supportedOrganisms(): Get the list of supported organisms for a given database

Retrieval of miRNA targets

The functions for obtaining and visualizing the target genes of differentially expressed miRNAs.

getTargets(): Get microRNA targets

mirnaTargets(): Explore miRNA-target pairs

Disease-SNPs association

The functions used to associate differentially expressed miRNAs with disease-related SNPs.

searchDisease(): Search for disease EFO identifiers

findMirnaSNPs(): Find disease-associated SNPs occurring at DE-miRNA loci

mirVariantPlot(): Create a trackplot to show the association between miRNAs and disease-SNPs

getEvidence(): Get the scientific evidence for a particular disease-SNP association

Integrate miRNA and gene expression

The functions for integrating miRNA and gene expression levels for both paired and unpaired samples.

batchCorrection(): Correct for batch effects in miRNA and gene expression measurements

mirnaIntegration(): Integrate microRNA and gene expression

integration(): Explore the results of the integration analysis between miRNAs and genes

plotCorrelation(): Plot correlation between miRNAs and genes within biological groups

Topological pathway analysis

The functions needed to perform a comprehensive topology-aware integrative pathway analysis (TAIPA) with MIRit.

integratedPathways(<IntegrativePathwayAnalysis>) integrationDatabase(<IntegrativePathwayAnalysis>) augmentedPathways(<IntegrativePathwayAnalysis>) show(<IntegrativePathwayAnalysis>): The IntegrativePathwayAnalysis class

listPathways(): List all the available biological pathways in KEGG, Reactome and WikiPathways

preparePathways(): Prepare miRNA-augmented pathways for integrative miRNA-mRNA pathway analyses

topologicalAnalysis(): Perform a topologically-aware integrative pathway analysis (TAIPA)

integratedPathways(): Access the results of integrative miRNA-mRNA pathway analyses

visualizeNetwork(): Visualize the relationships between miRNAs and genes in a biological pathway

integrationDotplot(): Display integrated miRNA-mRNA augmented pathways in a dotplot

augmentedPathways(): Access the miRNA-augmented pathways that were used during TAIPA

integrationDatabase(): Extract the database used for integrative miRNA-mRNA pathway analyses

The MirnaExperiment class