View source: R/plot_gene_set.R
plot_gene_set | R Documentation |
This function simply visualizes the gene expression profiles of
a defined subset of genes stored in the input ExpressionSet
. The maximum nummber of genes to visualize
at once is 25.
plot_gene_set(
ExpressionSet,
gene_set,
get_subset = FALSE,
use_only_map = FALSE,
colors = NULL,
plot_legend = TRUE,
y_ticks = 6,
digits_ylab = 1,
line_width = 1,
point_size = 2,
add_expression_values = FALSE,
n_genes_for_distance = 1,
...
)
ExpressionSet |
a standard PhyloExpressionSet or DivergenceExpressionSet object. |
gene_set |
a character vector storing the gene ids for which gene expression profiles shall be visualized. |
get_subset |
a logical value indicating whether or not an |
use_only_map |
a logical value indicating whether instead of a standard |
colors |
colors for gene expression profiles. Default: |
plot_legend |
a logical value indicating whether gene ids should be printed as legend next to the plot. |
y_ticks |
a numeric value specifying the number of ticks to be drawn on the y-axis. |
digits_ylab |
a numeric value specifying the number of digits shown for the expression levels on the y-axis. |
add_expression_values |
a logical value indicating whether expression values should be displayed on the plot. |
n_genes_for_distance |
a numeric value specifying the number of top genes to be selected based on the highest distance sum. |
... |
additional parameters passed to |
This function simply visualizes or subsets the gene expression levels of a set of genes
that are stored in the input ExpressionSet
.
Hajk-Georg Drost and Filipa Martins Costa
SelectGeneSet
, PlotEnrichment
, DiffGenes
data(PhyloExpressionSetExample)
# the best parameter setting to visualize this plot:
# png("test_png.png",700,400)
PlotGeneSet(ExpressionSet = PhyloExpressionSetExample,
gene_set = PhyloExpressionSetExample[1:5, 2],
lty = 1,
lwd = 4,
xlab = "Ontogeny",
ylab = "Expression Level")
# dev.off()
# In case you would like to work with the expression levels
# of selected genes you can specify the 'get_subset' argument:
plot_gene_set(ExpressionSet = PhyloExpressionSetExample,
gene_set = PhyloExpressionSetExample[1:5, 2],
get_subset = TRUE)
# get a gene subset using only a phylostratihraphic map
ExamplePSMap <- PhyloExpressionSetExample[ , 1:2]
plot_gene_set(ExpressionSet = ExamplePSMap,
gene_set = PhyloExpressionSetExample[1:5, 2],
get_subset = TRUE,
use_only_map = TRUE)
# In case you want the expression values to appear for the 2 genes with a most differentiated profile
plot_gene_set(ExpressionSet = PhyloExpressionSetExample,
gene_set = PhyloExpressionSetExample[1:5, 2],
add_expression_values =T,
n_genes_for_distance = 2
)
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