Generate a table of top-ranked entities (nodes)

Generate a table of top-ranked nodes from the optimal resolution candidate of entities on a tree.

topNodes(
  object,
  n = 10,
  sort_by = NULL,
  sort_decreasing = FALSE,
  sort_by_absolute = FALSE,
  p_value = 1
)

Arguments

object

An output object from evalCand.

n

An integer, the maximum number of entities to return.

sort_by

A character string specifying the column of object$output to sort by. Set to NULL to return without sorting.

sort_decreasing

A logical value indicating whether to sort by decreasing value of the sort_by column.

sort_by_absolute

A logical value indicating whether to take the absolute value of the sort_by column before sorting.

p_value

A numeric cutoff value for adjusted p-values. Only entities with adjusted p-values equal or lower than specified are returned.

Value

A data.frame with test results. The node column stores the node number for each entity.

Author

Ruizhu Huang, Charlotte Soneson

Examples

suppressPackageStartupMessages({
    library(TreeSummarizedExperiment)
    library(ggtree)
})

data(tinyTree)
ggtree(tinyTree, branch.length = "none") +
   geom_text2(aes(label = node)) +
   geom_hilight(node = 13, fill = "blue", alpha = 0.3) +
   geom_hilight(node = 18, fill = "orange", alpha = 0.3)

set.seed(1)
pv <- runif(19, 0, 1)
pv[c(seq_len(5), 13, 14, 18)] <- runif(8, 0, 0.001)

fc <- sample(c(-1, 1), 19, replace = TRUE)
fc[c(seq_len(3), 13, 14)] <- 1
fc[c(4, 5, 18)] <- -1
df <- data.frame(node = seq_len(19),
                 pvalue = pv,
                 logFoldChange = fc)
ll <- getCand(tree = tinyTree, score_data = df,
               node_column = "node",
               p_column = "pvalue",
               sign_column = "logFoldChange")
cc <- evalCand(tree = tinyTree, levels = ll$candidate_list,
               score_data = df, node_column = "node",
               p_column = "pvalue", sign_column = "logFoldChange",
               limit_rej = 0.05)

## Unsorted result table
topNodes(cc)
#>   node       pvalue logFoldChange        adj.p signal.node
#> 1    6 8.983897e-01            -1 9.446753e-01       FALSE
#> 2    7 9.446753e-01             1 9.446753e-01       FALSE
#> 3    8 6.607978e-01            -1 9.251169e-01       FALSE
#> 4    9 6.291140e-01            -1 9.251169e-01       FALSE
#> 5   10 6.178627e-02             1 1.441680e-01       FALSE
#> 6   13 2.672207e-04             1 9.352723e-04        TRUE
#> 7   18 1.339033e-05            -1 9.373233e-05        TRUE

## Sort by p-value in increasing order
topNodes(cc, sort_by = "pvalue")
#>   node       pvalue logFoldChange        adj.p signal.node
#> 1   18 1.339033e-05            -1 9.373233e-05        TRUE
#> 2   13 2.672207e-04             1 9.352723e-04        TRUE
#> 3   10 6.178627e-02             1 1.441680e-01       FALSE
#> 4    9 6.291140e-01            -1 9.251169e-01       FALSE
#> 5    8 6.607978e-01            -1 9.251169e-01       FALSE
#> 6    6 8.983897e-01            -1 9.446753e-01       FALSE
#> 7    7 9.446753e-01             1 9.446753e-01       FALSE