Plot the Expression Profiles of a Gene Set

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.

Usage

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,
  ...
)

Arguments

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 ExpressionSet subset of the selected gene_set should be retuned.
use_only_map: a logical value indicating whether instead of a standard ExpressionSet only a Phylostratigraphic Map or Divergene Map is passed to the function.
colors: colors for gene expression profiles. Default: colors = NULL, hence default colours are used.
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 matplot.

Details

This function simply visualizes or subsets the gene expression levels of a set of genes that are stored in the input ExpressionSet.

Author

Hajk-Georg Drost and Filipa Martins Costa

Examples

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")
#> Error in PlotGeneSet(ExpressionSet = PhyloExpressionSetExample, gene_set = PhyloExpressionSetExample[1:5,     2], lty = 1, lwd = 4, xlab = "Ontogeny", ylab = "Expression Level"): could not find function "PlotGeneSet"

# 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)
#> # A tibble: 5 × 5
#>   Phylostratum GeneID      Stage    Expression distance_sum
#>          <int> <fct>       <fct>         <dbl>        <dbl>
#> 1            1 at1g01040.2 Zygote        2174.      243600.
#> 2            1 at1g01050.1 Quadrant      1817.      237017.
#> 3            1 at1g01070.1 Torpedo        864.      238465.
#> 4            1 at1g01080.2 Mature         861.      238563.
#> 5            1 at1g01090.1 Bent         66980.     2075607.
#> Scale for y is already present.
#> Adding another scale for y, which will replace the existing scale.

#>   Phylostratum      GeneID    Zygote   Quadrant  Globular      Heart   Torpedo
#> 1            1 at1g01040.2  2173.635  1911.2001  1152.555  1291.4224  1000.253
#> 2            1 at1g01050.1  1501.014  1817.3086  1665.309  1564.7612  1496.321
#> 3            1 at1g01070.1  1212.793  1233.0023   939.200   929.6195   864.218
#> 4            1 at1g01080.2  1016.920   936.3837  1181.338  1329.4734  1392.643
#> 5            1 at1g01090.1 11424.567 16778.1685 34366.649 39775.6405 56231.569
#>         Bent    Mature
#> 1   962.9772 1696.4274
#> 2  1114.6435 1071.6555
#> 3   877.2060  894.8189
#> 4  1287.9746  861.2605
#> 5 66980.3673 7772.5617


# 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)
#> Error: measure variables not found in data: NA
            
# 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
            )
#> # A tibble: 5 × 5
#>   Phylostratum GeneID      Stage    Expression distance_sum
#>          <int> <fct>       <fct>         <dbl>        <dbl>
#> 1            1 at1g01040.2 Zygote        2174.      243600.
#> 2            1 at1g01050.1 Quadrant      1817.      237017.
#> 3            1 at1g01070.1 Torpedo        864.      238465.
#> 4            1 at1g01080.2 Mature         861.      238563.
#> 5            1 at1g01090.1 Bent         66980.     2075607.
#> Scale for y is already present.
#> Adding another scale for y, which will replace the existing scale.