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Compare IP enrichment across two treatment conditions in a single scatter plot

Source: R/ptrap_volcano2.R
ptrap_volcano2.Rd

When you have run ptrap_de() for two treatment groups (e.g., pair-bonded and non-bonded animals) in the same brain region, looking at two separate volcano plots makes it hard to see which genes behave similarly or differently across conditions. This function places both results on a single 2D scatter: the logFC (IP vs. input) of condition 1 on the y-axis and condition 2 on the x-axis. Each point is one gene.

Usage

ptrap_volcano2(
  de_result_1,
  de_result_2,
  fdr = TRUE,
  lfc_threshold = 1,
  fdr_threshold = 0.05,
  gene_col = "Gene",
  treatment_col = "treatment",
  region_col = "BrainRegion",
  colors = NULL,
  point_size = 3.5,
  point_alpha = 0.7,
  genes.annot = NULL,
  max_overlaps = 20,
  title = NULL,
  interactive = FALSE
)

Arguments

de_result_1

A tibble returned by ptrap_de() for the first treatment condition (plotted on the y-axis).

de_result_2

A tibble returned by ptrap_de() for the second treatment condition (plotted on the x-axis).

fdr

Logical. If TRUE (default), significance is assessed using the FDR column (BH-adjusted p-values). If FALSE, the raw PValue column is used instead.

lfc_threshold

Minimum absolute log2 fold change required to classify a gene as differentially expressed in a given condition (also sets the vertical and horizontal threshold lines). Default is 1.

fdr_threshold

P-value cutoff used to classify genes as DE. Applied to FDR when fdr = TRUE and to PValue when fdr = FALSE. Default is 0.05.

gene_col

Name of the column containing gene identifiers in both result tibbles. Default is "Gene".

treatment_col

Name of the column containing the treatment label in both result tibbles. Used to auto-generate axis labels and DE class names. Default is "treatment".

region_col

Name of the column containing the brain region label. Used to set the default plot title. Default is "BrainRegion".

colors

A named character vector mapping each DE class to a colour. Names must be "DE in both", "DE only <t1>", and "DE only <t2>", where <t1> / <t2> are the treatment names found in the data (e.g., "DE only pb" and "DE only sol"). See the examples for a template. If NULL (default), a colourblind-friendly palette is used.

point_size

Size of the points. Default is 3.5.

point_alpha

Opacity of the coloured (significant) points. Default is 0.7.

genes.annot

Character vector of gene names to label on the plot via ggrepel::geom_text_repel() (static mode only). Names must match values in the column specified by gene_col; an error is raised if any names are not found. Default is NULL (no labels).

max_overlaps

Passed to ggrepel::geom_text_repel(). Controls how many overlapping labels are allowed before they are hidden. Default is 20.

title

Plot title. If NULL (default), the brain region name extracted from de_result_1 is used.

interactive

Logical. If TRUE, returns an interactive plotly::ggplotly() object with hover tooltips showing gene name, logFC for each condition, p-value, and FDR. Gene labels (genes.annot) are omitted in this mode. Default FALSE.

Value

A ggplot2::ggplot() object, or a plotly object when interactive = TRUE.

Details

Reading the plot:

  • Genes near the diagonal (y = x dotted line) are equally enriched in both conditions.

  • Genes above the diagonal are more enriched in condition 1; genes below are more enriched in condition 2.

  • Genes that pass the fold-change and p-value thresholds in both conditions, or in only one, are highlighted in distinct colours. Genes that fail in both are shown in grey.

Significance uses FDR-adjusted p-values by default (fdr = TRUE); set fdr = FALSE to use raw p-values instead. The DE classification is recomputed inside this function from the supplied thresholds, so you can explore different cutoffs without re-running ptrap_de().

Examples

if (FALSE) { # \dontrun{
res_pb  <- ptrap_de(counts_mat, sample_df, gene_ids,
                    region_name = "POA", treatment_name = "pb")
res_sol <- ptrap_de(counts_mat, sample_df, gene_ids,
                    region_name = "POA", treatment_name = "sol")

# Default plot — FDR on both axes
ptrap_volcano2(res_pb, res_sol)

# Use raw p-values for the DE classification
ptrap_volcano2(res_pb, res_sol, fdr = FALSE)

# Interactive with hover tooltips
ptrap_volcano2(res_pb, res_sol, interactive = TRUE)

# Custom thresholds, title and colours
ptrap_volcano2(res_pb, res_sol,
               lfc_threshold = 0.5,
               fdr_threshold = 0.1,
               title         = "POA: pb vs sol",
               colors        = c("DE in both"  = "#D55E00",
                                 "DE only pb"  = "#0072B2",
                                 "DE only sol" = "#49a15f"))
} # }