MIGSAres-plots: MIGSAres plots
In MIGSA: Massive and Integrative Gene Set Analysis

Description Usage Arguments Value See Also Examples

genesHeatmap plots a heatmap with the number of experiments in which each gene contributed to enrich each gene set. genesBarplot generates a barplot of the number of gene sets in which each gene contributed to enrich. Each gene set counts 1 regardless if it was enriched in many experiments. x-axis each gene, y-axis number of gene sets in which it contributed to enrich. migsaHeatmap plots the enrichment heatmap of the MIGSAres object. Additionally, given the categories sets list, for each set of categories, it is shown the number of experiments that make up each category (#exps), the number of gene sets enriched by at least one experiment (>= 1), and the number of gene sets enriched by at least 25, 50, 75, and 100 geneSetBarplot generates a barplot of the number of experiments in which each gene set was enriched. x-axis each gene set, y-axis times it was enriched (0 to #experiments).

`MIGSAres-plots`(migsaRes)

genesHeatmap(migsaRes, ...)

## S4 method for signature 'MIGSAres'
genesHeatmap(
  migsaRes,
  enrFilter = 0,
  gsFilter = 0,
  colPal = c("white", "red"),
  col.dist = NA,
  row.dist = NA,
  layout = NA,
  dendrogram = "row"
)

genesBarplot(migsaRes, ...)

## S4 method for signature 'MIGSAres'
genesBarplot(migsaRes, enrFilter = 0, gsFilter = 0)

migsaHeatmap(migsaRes, ...)

## S4 method for signature 'MIGSAres'
migsaHeatmap(
  migsaRes,
  enrFilter = 0,
  expFilter = 0,
  categories = list(),
  categLabels = TRUE,
  colPal = c("white", "red"),
  col.dist = NA,
  row.dist = NA,
  layout = NA,
  remove0Rows = TRUE,
  breaks = NA
)

## S4 method for signature 'matrix'
migsaHeatmap(
  migsaRes,
  categories = list(),
  categLabels = TRUE,
  colPal = c("white", "red"),
  col.dist = NA,
  row.dist = NA,
  layout = NA
)

geneSetBarplot(migsaRes, ...)

## S4 method for signature 'MIGSAres'
geneSetBarplot(migsaRes, enrFilter = 0)

`migsaRes`	MIGSAres object.
`...`	not in use.
`enrFilter`	numeric. Keep gene sets enriched in at least enrFilter experiments.
`gsFilter`	numeric. Keep genes enriched in at least gsFilter gene sets.
`colPal`	vector. Character vector of two colors, first value will represent FALSE/1 on heatmap, and second value TRUE/0.
`col.dist`	character. Distance algorithm to be used in columns, passed to vegdist function. If migsaRes has cutoff then default is jaccard, else, default is euclidean.
`row.dist`	character. Distance algorithm to be used in rows, passed to vegdist function. If migsaRes has cutoff then default is jaccard, else, default is euclidean.
`layout`	matrix. The layout used for heatmaps.
`dendrogram`	character. Wheter to plot "row", "col", "none" or "both" dendrograms.
`expFilter`	numeric. Keep experiments which enriched at least expFilter gene sets.
`categories`	list. List of character vectors, each vector must have the same length as the number of experiments (ncol(migsaRes)-3). It will plot for each category/column a color representing its category.
`categLabels`	logical. Indicates if labels should be plotted for each category.
`remove0Rows`	logical. Whether remove gene sets that are not enriched in any experiment.
`breaks`	numeric. If migsaRes does not have cutoff then break P-values in breaks intervals.

In heatmap functions: A list returned by heatmap.2 function (plotted data). In other functions: A ggplot object used as graphic.

setEnrCutoff

data(migsaRes)
## For this example lets work with the first 50 results
migsaRes <- migsaRes[1:50, ]
#### genesHeatmap
## First lets set a cutoff of 0.1
migsaResWCoff <- setEnrCutoff(migsaRes, 0.1)
## Lets check what genes contributed to enrich the highest number of gene
## sets (in more than one gene set).
genesHeatmap(migsaResWCoff, gsFilter = 1)
## Moreover we can keep gene sets which where enriched in more than
## enrFilter experiments. To do this, we can use the enrFilter parameter.

#### genesBarplot
## Lets set a cutoff of 0.01
migsaResWCoff <- setEnrCutoff(migsaRes, 0.01)
## Lets check what genes contributed to enrich the highest number of gene
## sets (in more than one gene set).
genesBarplot(migsaResWCoff, gsFilter = 1)
## Moreover we can keep gene sets which where enriched in more than
## enrFilter experiments. To do this, we can use the enrFilter parameter.

#### migsaHeatmap
## Lets set a cutoff of 0.1
migsaResWCoff <- setEnrCutoff(migsaRes, 0.1)
## Lets visually check enriched gene sets shared between experiments.
migsaHeatmap(migsaResWCoff)
#### geneSetBarplot
## Lets set a cutoff of 0.1
migsaResWCoff <- setEnrCutoff(migsaRes, 0.1)
## Lets check in how many experiments each gene set was enriched (in more
## than one experiment).
geneSetBarplot(migsaResWCoff, enrFilter = 1)