genomewide.log10q.plot: Genomewide log10q Plot

In GRIN2: Genomic Random Interval (GRIN)

Genomewide log10q Plot

Description

The function return a genome-wide plot based on -log(10) q-value of each of the evaluated annotated genes or lesion boundaries on each chromosome. The plot is lesion type specific (gain, loss, mutation, etc...).

Usage

genomewide.log10q.plot(
  grin.res,
  lsn.grps,
  lsn.colors = NULL,
  max.log10q = NULL
)

Arguments

grin.res	GRIN results evaluating annotated genes or lesion boundaries (output of the grin.stats function using either lesion boundaries or annotated genes as a marker input file).
lsn.grps	Selected lesion groups to be added to the plot.
lsn.colors	Colors assigned to each lesion group (if NULL, lesion colors will be assigned automatically using default.grin.colors function).
max.log10q	Maximum log10 q value to be added to the plot. All boundaries or genes with -log10 q smaller than this value will be set automatically to max.log10q.

Value

The function return a genome-wide plot based on -log(10) q-value of each of the evaluated annotated genes or lesion boundaries to be affected by a certain type of lesions (gain, loss, mutation, etc...).

Author(s)

Abdelrahman Elsayed [e-mail] and Stanley Pounds [e-mail]

See Also

grin.lsn.boundaries()

Examples

data(lesion.data)
data(hg19.gene.annotation)
data(hg19.chrom.size)

# This analysis is lesion type specific. So, user should first data extract data for a specific
# lesion group of interest for example gains from the lesion data file:
gain=lesion.data[lesion.data$lsn.type=="gain",]
# Return lesion boundaries for gains:
lsn.bound.gain=grin.lsn.boundaries(gain, hg19.chrom.size)
# Run GRIN analysis Using Lesion Boundaries as Markers Instead of the Gene Annotation File:
GRIN.results.gain.bound=grin.stats(gain, lsn.bound.gain, hg19.chrom.size)
# Return genomewide -log10q plot for association between lesion boundaries and gain:
genomewide.log10q.plot(GRIN.results.gain.bound, lsn.grps=c("gain"),
                       lsn.colors=c("gain" = "red"), max.log10q = 10)

# instead of lesion boundaries, users can also plot -log10q values for annotated genes using
# genes annotation data as a marker data file:
grin.results=grin.stats(lesion.data,
                        hg19.gene.annotation,
                        hg19.chrom.size)

genomewide.log10q.plot(grin.results, lsn.grps=c("gain"), lsn.colors=c("gain" = "red"),
                       max.log10q = 10)

# User can run this same analysis for other lesion types such as mutations and deletions.

GRIN2 documentation built on April 4, 2025, 1:41 a.m.