confeti: Main function to run CONFETI.

Description Usage Arguments Value

Description

Creating a sample covariance matrix based on non-genetic independent components.

Usage

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confeti(expr_data, snp_data, return_all = TRUE, cores = 1, k = NULL,
  var_cutoff = 95, ica_runs = 1, scale_pheno = FALSE,
  h_clust_cutoff = 0.3, similarity_measure = "peaks", threshold = 0.05,
  return_pval = FALSE)

Arguments

expr_data

Expression matrix with dimensions g x n.

snp_data

Genotype matrix with dimensions s x n.

return_all

If TRUE, the full ICA results are returned. If set FALSE only the sample covariance matrix and lower dimensional phenotype matrix are returned.

cores

Number of cores to use for genotype association testing, and ICA multi runs (if ica_runs \> 1).

k

Number of components to be estimated or method to estimate it.

var_cutoff

Percent variance threshold to use when <k_est> is not supplied.

ica_runs

Number of times to run ICA. If this is set to a number larger than 1, only ICs that replicate between runs are going to be returned

scale_pheno

If set to TRUE the pre-processing step of the data will include a scaling step. This will divide all phenotypes by their standard deviation.

h_clust_cutoff

is the cutoff value used in hierarchical clustering. Default is set to 0.3.

similarity_measure

How to measure the similarity between ICs.

threshold

Bonferroni significance threshold for genotype association testing

return_pval

If set to TRUE, p-values for genotype ICA association testing are returned

Value

N x N covariance structure matrix.


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