correlateWithBinaryPhenotype: Computes the association statistics between RER from...

In nclark-lab/RERconverge: Analysis of Convergence Between Organismal Traits and DNA/Protein Sequences

Computes the association statistics between RER from getAllResiduals and a phenotype paths vector for a binary phenotype made with tree2Paths

Description

Computes the association statistics between RER from getAllResiduals and a phenotype paths vector for a binary phenotype made with tree2Paths

Usage

correlateWithBinaryPhenotype(
  RERmat,
  charP,
  min.sp = 10,
  min.pos = 2,
  weighted = "auto",
  winsorizeRER = NULL,
  winsorizetrait = NULL,
  bootstrap = F,
  bootn = 1000
)

Arguments

RERmat	RER matrix returned by getAllResiduals
charP	phenotype vector returned by tree2Paths or char2Paths
min.sp	Minimum number of species that must be present for a gene
min.pos	Minimum number of species that must be present in the foreground (non-zero phenotype values)
weighted	perform weighted correlation. This option turns on weighted correlation that uses the weights computed by foreground2Tree(wholeClade=T). This setting will treat each clade a single observation for the purpose of p-value estimation. The function will guess automatically if the charP vector is of "weighted" type and there should be not need to set this parameter.
winsorizeRER	Winsorize RER values before computing Pearson correlation. winsorizeRER=3 will set the 3 most extreme RER values at each end of each row to the 4th most extreme value.
winsorizetrait	Winsorize phenotype vector values before computing Pearson correlation. winsorizeRER=3 will set the 3 most extreme RER values at each end of each row to the 4th most extreme value.
bootstrap	toggle bootstrapping (for weighted pearson correlation)
bootn	number of runs to use when bootstrapping. Will be ignored if bootstrap is false.

nclark-lab/RERconverge documentation built on June 9, 2025, 6:02 a.m.