z_summary {GWENA} | R Documentation

## Calculating Z summary

### Description

Use the topological metrics and permutations from output of `modulePreservation` to compute a Z summary (a composite preservation statistic) as defined by https://doi.org/10.1371/journal.pcbi.1001057

### Usage

    z_summary(observed_stat, permutations_array)

### Arguments

`observed_stat` | matrix, bidimensional matrix containing the topological matrix computed for each module by `modulePreservation` (the element `observed`). Modules are in row, metrics are in column.
`permutations_array` | matrix, tridimensional matrix containing the topological matrix computed for each module by `modulePreservation` (the element `observed`). Modules are in dim 1, metrics are in dim 2, permutations are in dim 3.

### Details

The original Zsummary composite preservation statistic was defined by Langfelder et al. (2011). However this method use the metric from `modulePreservation` since they it handle better large and multiple testing correction.

### Value

A named vector of the z summary statistic with the module id as name.

### Examples

    expr_by_cond <- list(cond1 = kuehne_expr[1:24, 1:350],
                         cond2 = kuehne_expr[25:48, 1:350])
    net_by_cond <- lapply(expr_by_cond, build_net, cor_func = "spearman",
                          n_threads = 1, keep_matrices = "both")

    mods_labels <- setNames(
      sample(1:6, 350, replace = TRUE,
             prob = c(0.05, 0.4, 0.25, 0.15, 0.1, 0.05)),
      colnames(expr_by_cond$cond1))

    netrep_res <- NetRep::modulePreservation(
      network = lapply(net_by_cond, `[[`, "adja_mat"),
      data = lapply(expr_by_cond, as.matrix),
      correlation = lapply(net_by_cond, `[[`, "cor_mat"),
      moduleAssignments = mods_labels,  nPerm = 100)

    z_summary(netrep_res$observed, netrep_res$nulls)

    mod_by_cond <- mapply(detect_modules, expr_by_cond,
                          lapply(net_by_cond, `[[`, "network"),
                          MoreArgs = list(detailled_result = TRUE),
                          SIMPLIFY = FALSE)

    comparison <- compare_conditions(expr_by_cond,
                                     lapply(net_by_cond, `[[`, "adja_mat"),
                                     lapply(net_by_cond, `[[`, "cor_mat"),
                                     lapply(mod_by_cond, `[[`, "modules"),
                                     n_perm = 100)

    z_summary(comparison$result$cond1$cond2$observed,
              comparison$result$cond1$cond2$nulls)

[Package GWENA version 1.2.0 Index]