DNLC_statistics: calculate t statistics for gene graph using DNLC method.
In ilab/DNLC: Differential Network Local Consistency Analysiss

Description Usage Arguments Details Value Examples

View source: R/DNLC.R

a function to calculate t statistics for genes in the graph.

1 2	DNLC_statistics(gene_graph, gene_expr = "x", clinic_data = "y", confounder_matrix = NULL, lmi_data = NULL)

`gene_graph`	graph of gene
`gene_expr`	expr of gene
`clinic_data`	patient data
`confounder_matrix`	other message describe clinic message
`lmi_data`	lmi data for each gene.

This function first calculates the matrix of local moran's I, and then conducts testing for the association of each gene's local moran's I with the clinical outcome variable. Clinical confounder variables such as age, gender etc can be included.

`all_gene_id`	gene ids in graph
`t_data`	t-data for each gene

## Not run: 
simulation <- init_simulation_gene_net()
t_data = DNLC_statistics(simulation$gene_graph, simulation$gene_expr,
  simulation$patient_matrix, lmi_data = simulation$lmi_matrix)
fdr_result <- gene_fdrtest(t_data)
sig_genes <- significant_genes(fdr_obj = fdr_result, thres = 0.2)

## End(Not run)