getCand: Generate candidates for different thresholds

In fionarhuang/treeclimbR: An algorithm to find optimal signal levels in a tree

Generate candidates for different thresholds

Description

Generate candidates for different thresholds (t). A candidate consists of a disjoint collection of leaves and internal branches, that collectively cover all leaves in the tree, and represents a specific aggregation pattern along the tree.

Usage

getCand(
  tree,
  t = NULL,
  score_data,
  node_column,
  p_column,
  sign_column,
  threshold = 0.05,
  pct_na = 0.5,
  message = FALSE
)

Arguments

tree	A phylo object.
t	A vector of threshold values used to search for candidates, in the range [0, 1]. The default (NULL) uses a sequence c(seq(0, 0.04, by = 0.01), seq(0.05, 1, by = 0.05))
score_data	A data.frame including at least one column with node IDs (specified with the node_column argument), one column with p-values (specified with the p_column argument) and one column with directions of change (specified with the sign_column argument).
node_column	The name of the column of score_data that contains the node information.
p_column	The name of the column of score_data that contains p-values for nodes.
sign_column	The name of the column of score_data that contains the direction of change (e.g., the log-fold change). Only the sign of this column will be used.
threshold	Numeric scalar; any internal node where the value of the p-value column is above this value will not be returned. The default is 0.05. The aim of this threshold is to avoid arbitrarily picking up internal nodes without true signal.
pct_na	Numeric scalar. In order for an internal node to be eligible for selection, more than pct_na of its direct child nodes must have a valid (i.e., non-missing) value in the p_column column. Hence, increasing this number implies a more strict selection (in terms of presence of explicit values).
message	A logical scalar, indicating whether progress messages should be printed to the console.

Value

A list with two elements: candidate_list and score_data. condidate_list is a list of candidates obtained for the different thresholds. score_data is a data.frame that includes columns from the input score_data and additional columns with q-scores for different thresholds.

Author(s)

Ruizhu Huang

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)

## Simulate p-values and directions of change for nodes
## (Nodes 1, 2, 3, 4, 5, 13, 14, 18 have a true signal)
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,
              t = c(0.01, 0.05, 0.1, 0.25, 0.75),
              node_column = "node", p_column = "pvalue",
              sign_column = "logFoldChange")

## Candidates
ll$candidate_list

## Score table
ll$score_data

fionarhuang/treeclimbR documentation built on May 19, 2024, 1:18 p.m.