plotOverview: Plot a karyotype overview of the genome with the identified...

Description Usage Arguments Value Author(s) See Also Examples

Description

Plots an overview of the genomic locations of the identified regions (see calculatePvalues) in a karyotype view. The coloring can be done either by significant regions according to their p-values, significant by adjusted p-values, or by annotated region if using matchGenes.

Usage

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plotOverview(regions, annotation = NULL, type = "pval",
  significantCut = c(0.05, 0.1), ...)

Arguments

regions

The $regions output from calculatePvalues.

annotation

The output from running matchGenes on the output from calculatePvalues. It is only required if type='annotation'.

type

Must be either pval, qval, fwer or annotation. It determines whether the plot coloring should be done according to significant p-values (<0.05), significant q-values (<0.10), significant FWER adjusted p-values (<0.05) or annotation regions.

significantCut

A vector of length two specifiying the cutoffs used to determine significance. The first element is used to determine significance for the p-values and the second element is used for the q-values.

...

Arguments passed to other methods and/or advanced arguments. Advanced arguments:

base_size

Base point size of the plot. This argument is passed to element_text (size argument).

areaRel

The relative size for the area label when type='pval' or type='qval'. Can be useful when making high resolution versions of these plots in devices like CairoPNG.

legend.position

This argument is passed to theme. From ggplot2: the position of legends. ('left', 'right', 'bottom', 'top', or two-element numeric vector).

Passed to extendedMapSeqlevels.

Value

A ggplot2 plot that is ready to be printed out. Tecnically it is a ggbio object.

Author(s)

Leonardo Collado-Torres

See Also

calculatePvalues, matchGenes

Examples

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## Construct toy data
chrs <- paste0('chr', c(1:22, 'X', 'Y'))
chrs <- factor(chrs, levels=chrs)
library('GenomicRanges')
regs <- GRanges(rep(chrs, 10), ranges=IRanges(runif(240, 1, 4e7), 
    width=1e3), significant=sample(c(TRUE, FALSE), 240, TRUE, p=c(0.05, 
    0.95)), significantQval=sample(c(TRUE, FALSE), 240, TRUE, p=c(0.1, 
    0.9)), area=rnorm(240))
annotation <- data.frame(region=sample(c('upstream', 'promoter', 
    "overlaps 5'", 'inside', "overlaps 3'", "close to 3'", 'downstream'), 
    240, TRUE))

## Type pval
plotOverview(regs)

## Not run: 
## Type qval
plotOverview(regs, type='qval')

## Annotation
plotOverview(regs, annotation, type='annotation')

## Resize the plots if needed.

## You might prefer to leave the legend at ggplot2's default option: right
plotOverview(regs, legend.position='right')

## Although the legend looks better on the bottom
plotOverview(regs, legend.position='bottom')

## Example knitr chunk for higher res plot using the CairoPNG device
```{r overview, message=FALSE, fig.width=7, fig.height=9, dev='CairoPNG', dpi=300}
plotOverview(regs, base_size=30, areaRel=10, legend.position=c(0.95, 0.12))
```

## For more custom plots, take a look at the ggplot2 and ggbio packages
## and feel free to look at the code of this function:
plotOverview

## End(Not run)


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