Integrate miRNA and gene expression data with MIRit
Introduction | What is MIRit | How to cite MIRit | Installation | Data preparation | Load example data | Paired vs unpaired data | Set up expression matrices | Define sample metadata | Create a MirnaExperiment object | Differential expression analysis | Visualize expression variability | Perform miRNA and gene differential expression | Available methods for RNA-Seq and microarrays | Model design | The performMirnaDE() and performGeneDE() functions | Advanced parameters | Add differential expression results from other technologies | Visualize differentially expressed features | Access differential expression tables | Create a volcano plot for miRNAs and genes | Produce differential expression bar plots | Functional enrichment analysis | Available approaches: ORA, GSEA and CAMERA | Available databases and categories | Supported species | Perform functional enrichment with the enrichGenes() function | Visualize enriched sets | Access results table | Enrichment dot plots and bar plots | Other plots for GSEA | Retrieve miRNA targets | Databases with miRNA-mRNA interactions | The mirDIP approach | Download predicted and validated interactions with getTargets() | Assess the effects of miRNAs on target genes | Correlation analysis for paired data | Statistical correlation coefficients | Perform a correlation analysis in MIRit | Account for the group effect in correlation analysis | Explore the succesfully integrated miRNA-target pairs | Visualize the correlation between miRNAs and genes | Association tests for unpaired data | Fisher's exact test | Boschloo's exact test | Perform one-sideded association tests in MIRit | Rotation gene-set tests for unpaired data | Session info | References
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