get_independent_relevant_phenotypes: Identify independent relevant phenotypes

In SciOmicsLab/PhenoComb: Phenotype Combinatorial Analysis

Identify independent relevant phenotypes

Description

It uses a network clustering process to identify most representative phenotypes when several similar phenotypes are relevant.

Usage

get_independent_relevant_phenotypes(
  phen_data,
  channel_data,
  n_phenotypes = 1000,
  min_confidence = 0.5,
  max_pval = NULL,
  n_threads = 1
)

Arguments

phen_data	A Data.Frame with Marker columns, sample columns, and (effect_size, p_value, log2foldChange) columns.
channel_data	Data.Frame containing columns named: Channel, Marker, T1, [T2, T3, ... , Tn], [OOB].
n_phenotypes	maximum number of phenotypes to be considered from phen_data filtered by lowest p-values. Default: 1000.
min_confidence	Minimal confidence threshold to filter output. Default: 0.5.
max_pval	Apply a p-value filter before computing independent phenotypes.
n_threads	Number of threads to be used. Default: 1.

SciOmicsLab/PhenoComb documentation built on Aug. 26, 2023, 1:28 p.m.