Description Usage Arguments Details Value References Examples
Generate the plot from the processed GenomicOZone dataset object, including genome plots, chromosome plots and zone plots.
1 2 3 4 5 6 7 8 9 10 11 | plot_genome(GOZ.ds, plot.file,
alpha = 0.05, min.effect.size = 0.8,
plot.width = NULL, plot.height = NULL)
plot_chromosomes(GOZ.ds, plot.file,
alpha = 0.05, min.effect.size = 0.8,
plot.width = NULL, plot.height = NULL)
plot_zones(GOZ.ds, plot.file,
alpha = 0.05, min.effect.size = 0.8,
log.exp = TRUE, plot.all.zones = FALSE)
|
GOZ.ds |
a GenomicOZong dataset object after running |
plot.file |
a output file name. The file type is "pdf". |
alpha |
a cutoff for selecting adjuted |
min.effect.size |
the minimum effect size required for an outstanding zone. The effect size for ANOVA ranging from 0 to 1 is calculated by R package sjstats \insertCitesjstats2019GenomicOZone. Default to 0.8. |
plot.width |
a numerical number to specify the width of page in the plot. Using |
plot.height |
a numerical number to specify the height of page in the plot. Using |
log.exp |
a logical indicating whether to use log-scaled activity in the plot. |
plot.all.zones |
a logical indicating whether to plot all zones into the file. If |
The three functions plot visualizations of the genome, chromosomes and zones. The R packages ggplot2
\insertCiteWickham2016ggplot2GenomicOZone and ggbio
\insertCiteyin2012ggbioGenomicOZone are used to generate the plots.
The function plot_genome
plots the genome-wide overviews with marked significant differential zones.
The function plot_chromosomes
plots the chromosome-wide heatmap of normalized and linearized activity between sorted zones and samples, visualizing the zones with significant ones marked.
The function plot_zones
plots the line chart and box-plot of the activity of the genes within each significant zone, visualizing gene activity changes over sample conditions.
The function takes an input of a object, which has been created by GOZDataSet
and and processed by GenomicOZone
. The functions accesse the object and generate visualizations. See GOZDataSet
for how to create the input object. See GenomicOZone
for how to process the input object and perform the analysis.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | # Create an example of GOZ.ds
data <- matrix(c(1,5,2,6,5,1,6,2), ncol = 2, byrow = TRUE)
rownames(data) <- paste("Gene", 1:4, sep='')
colnames(data) <- paste("Sample", c(1:2), sep='')
colData <- data.frame(Sample_name = paste("Sample", c(1:2), sep=''),
Condition = c("Cancer", "Normal"))
design <- ~ Condition
rowData.GRanges <- GRanges(seqnames = Rle(rep("chr1", 4)),
ranges = IRanges(start = c(1,2,3,4), end = c(5,6,7,8)))
names(rowData.GRanges) <- paste("Gene", 1:4, sep='')
ks <- c(2)
names(ks) <- "chr1"
GOZ.ds <- GOZDataSet(data, colData, design,
rowData.GRanges = rowData.GRanges,
ks = ks)
####
# Run the zoing process
GOZ.ds <- GenomicOZone(GOZ.ds)
####
# Generate plots
plot_genome(GOZ.ds, plot.file = "Test_genome.pdf",
plot.width = 15, plot.height = 4)
plot_chromosomes(GOZ.ds, plot.file = "Test_chromosome.pdf",
plot.width = 20, plot.height = 4)
plot_zones(GOZ.ds, plot.file = "Test_zone.pdf",
plot.all.zones = FALSE)
|
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