run_ica: Custom ICA function for analyzing gene expression data.

In jinhyunju/icreport: Tools for creating a visual summary of matrix decomposition results.

Description

Performing ICA on a dataset and create a list object with results.

Usage

run_ica(pheno_mx = NULL, k_est = NULL, var_cutoff = 99, n_runs = 1,
  n_cores = NULL, scale_pheno = FALSE, h_clust_cutoff = 0.3,
  max_iter = 10, cor_threshold = 0.05, similarity_measure = "peaks")

Arguments

pheno_mx	Phenotype matrix with diemnsions g x N
k_est	Number of components to be estimated or method to estimate it.
n_runs	Number of runs for estimating k. Default value is set to 5.
n_cores	Number of cores to be used for estimating k. Default is set to 1.
scale_pheno	Logical value specifying the scaling of row of the pheno_mx.
h_clust_cutoff	is the cutoff value used in hierarchical clustering. Default is set to 0.3.
max_iter	Maximum iterations for estimating k for each run. Default value is set to 10.
cor_threshold	Threshold for significant correlation calling. Default is set to 0.05.
similarity_measure	How to measure the similarity between ICs. If set to "peaks" only gene weights that are greater than 1 sd are used to calculate similarity.

Value

List with the following entries.

jinhyunju/icreport documentation built on May 19, 2019, 10:35 a.m.