score_func: The main function for the score calculation.

In terrysun0302/FastMix: An OLS-based approach for fitting LMER with applications to gene expression deconvolution analysis

Description

A function for discriminant analysis after the FaxtMix analysis.

Usage

  score_func(mod1, Data_0, Data_1, Response_interaction_index,
Response_idx, sig.level=0.05)

Arguments

mod1	An object from FastMix model using training data.
Data_0	See the function DataPrep_test().
Data_1	See the function DataPrep_test().
Response_interaction_index	The indexs of the interaction term between resposne and other variables in Data_0 and Data_1.
Response_idx	The indexs of the resposne response variables in Data_0 and Data_1.
sig.level	By design, the sparse scores are linear combinations of genes that have significant interactions with the response. 'sig.level' is the significance level that defines those significant genes. Default to 0.05.

Value

single_score	A single summary score using all genes.
single_sparse_score	A single summary score using selected genes.
multi_score	Multiple summary scores using all genes.
multi_sparse_score	Multiple summary scores using only genes with significant interactions with the response variable. Note that the first row (with rowname 'fixed') represents the collective discriminant information of the fixed effects.

Author(s)

Hao Sun

terrysun0302/FastMix documentation built on Nov. 14, 2019, 4:54 a.m.