Compare preservation statistics

Compares the two topology-based preservation statistics - correlation of adjacencies (cor_adj) and correlation of intramodular connectivities (cor_kIM) - in terms of their ability to distinguish actual modules from random ones and to capture the expected decrease in module preservation with increasing phylogenetic distance.

Usage

comparePresStats(
  pres_stats,
  random_pres_stats,
  tree,
  colors = NULL,
  font_size = 14
)

Arguments

pres_stats

Data frame of the preservation statistics for the actual (pruned) modules. Required columns:

regulator

Character, transcriptional regulator.

replicate1, replicate2

Character, the names of the replicates compared.

species1, species2

Character, the names of the species replicate1 and replicate2 belongs to, respectively.

cor_adj

Numeric, correlation of adjacencies per module and replicate pair.

cor_kIM

Numeric, correlation of intramodular connectivities per module and replicate pair.

random_pres_stats

Data frame of the preservation statistics for the random modules. Required columns:

regulator

Character, transcriptional regulator.

replicate1, replicate2

The names of the replicates compared.

species1, species2

The names of the species replicate1 and replicate2 belongs to, respectively.

cor_adj

Numeric, correlation of adjacencies per random module and replicate pair.

cor_kIM

Numeric, correlation of intramodular connectivities per random module and replicate pair.

tree

Object of class phylo, the phylogenetic tree of the species.

colors

Character vector of length 2, the colors for cor_adj and cor_kIM.

font_size

Numeric, font size (default: 14).

Value

A boxplot as a ggplot object comparing how well each preservation statistic can distinguish actual and random modules and capture phylogenetic information.

Details

As part of the CroCoNet approach, pairwise module preservation scores are calculated between replicates, both within and across species (see calculatePresStats) to gain information about the cross-species differences but also about the within-species diversity of the modules. These correlation-based preservation statistics quantify how well the module topology is preserved between the networks of two replicates. While cor_adj compares fine-grained topology at the level of adjacencies per edge, cor_kIM compares higher-level topology based on intramodular connectivities, gene-level summaries of the individual adjacencies. The statistics are calculated not just for the actual, biologically meaningful modules, but also for random modules with matching sizes.

The function plots two distributions for both cor_adj and cor_kIM: 1) the difference in preservation between each actual and corresponding random module, and 2) the inverse correlation between preservation and phylogenetic distance for each actual module. The higher these values are, the better the preservation statistic perfoms, since the actual modules are expected to be more preserved than the random modules, and all modules, but especially the actual ones, are expected to be more preserved between closely related species than between phylogenetically distant species. By comparing the distributions between cor_adj and cor_kIM, the user can select the better preservation statistic for the downstream steps of the workflow (tree reconstruction and quantification of module conservation).

See also

Other functions to plot preservation statistics: plotPresStatDistributions(), plotPresStats()

Examples

comparePresStats(pres_stats, random_pres_stats, tree)