violinPlot: Compare groups within a single dataset in a violin plot
In MetaIntegrator: Meta-Analysis of Gene Expression Data

Description Usage Arguments Details Value Author(s) See Also Examples

Given a filterObject and a datasetObject this function will use the selected genes of the filterObject to calculate and compare the z-scores of the groups (e.g. cases vs. controls) from the datasetObject by generating a violin plot. A violin plot is similar to a box plot, except the width of each violin is proportional to the density of points. violinPlot() is commonly used to validate a gene signature in an independent dataset.

1
2
3

violinPlot(filterObject, datasetObject, labelColumn = "label",
  comparisonMethod = "wilcox.test", pairwiseComparisons = TRUE,
  autoLineBreak = TRUE)

`filterObject`	a MetaFilter object containing the signature genes that will be used for the z-score calculation
`datasetObject`	a Dataset object (typically independent validation dataset) for group comparison in a violin plot
`labelColumn`	the label of the column in `$pheno` that specifies the groups to compare, typically case or control (default: 'label')
`comparisonMethod`	statistical test that will be used (default="wilcox.test"). Other options include "t.test".
`pairwiseComparisons`	if TRUE, perform pairwise statistical comparisons against the first factor level. If FALSE, perform global statistical comparisons (default: TRUE).
`autoLineBreak`	if TRUE, insert line breaks into labels on plots. If FALSE, don't insert line breaks (default: TRUE)

The z-score is based off of the geometric mean of expression. As such, negative expression values are not allowed. A dataset is thus always scaled by its minimum value + 1, such that the lowest value = 1. Any individual NANs or NAs are also set to 1. If a dataset does not have any information on a given gene, the entire gene is simply left out of the score.

Returns a violin plot as ggplot2 plot object

Winston A. Haynes

filterGenes, runMetaAnalysis

1
2
3

violinPlot(tinyMetaObject$filterResults$pValueFDR0.05_es0_nStudies1_looaTRUE_hetero0, 
   tinyMetaObject$originalData$Whole.Blood.Study.1, 
     labelColumn="group")