spinglass_procedure: Generate modules from seed genes using Spinglass community...

In lanagarmire/NMFEM: Non-negative Matrix Factorization analysis and module generation for scRNA-Seq data

Description

Generate modules from seed genes using Spinglass community detection method

Usage

spinglass_procedure(expr_matrix_, grouping_vec_, selected_genes_, ppi_edges_,
  organism_, log_transformation_ = T, verbose_level_ = 1,
  n_top_modules_ = 5, n_threads_ = 1, min_size_ = 10, max_size_ = 100,
  enrichment_analysis_ = "GO", gamma_ = 0.5, seed_ = 12345, ...)

Arguments

expr_matrix_	The expression matrix, each row is a gene and each column is a sample. The row names should be gene symbols and the column names should be sample ids. Use the correct capticalization for gene symbols. For mouse genes,only the first letter is capitalized (e.g. Tp53); for human genes, all letters are capitalized (e.g. TP53). The values will be log-transformed by default, this can be changed using the log_transofrmation_ option.
grouping_vec_	A factor vector, indicating the groupping. Its length should be the same as the number of columns in expr_matrix_. Example: factor(c(1,1,1,2,2,2,2,2,2))
selected_genes_	A character vector. The genes that are used as seed genes in the FEM algorithm. Typically generated from another method such as NMF.
ppi_edges_	A data.frame containing all the protein-protein interactions (PPI). It should have two columns of gene symbols, each row indicating a pair of genes that have interaction. data(hppi) and data(mppi) are two example PPI networks, respectively for humans and mice.
organism_	Either "human" or "mouse".
log_transformation_	Whether to log-transform the expression matrix. A pseudo count 1 will be added to each value before log transformation to avoid infinity. That is, expr_matrix_ <- log(expr_matrix_+1). Default: True.
verbose_level_	How much information is printed. Either 0, 1 or 2, default: 1.
n_top_modules_	Number of top modules to pick. Default: 5.
n_threads_	Number of threads to use. Default: 1.
min_size_	Module size lower cut-off. Default: 10.
max_size_	Module size upper cut-off. Default: 100.
enrichment_analysis_	Either "GO" or "KEGG".
seed_	Random seed.
...	Additional parameters for KEGG_analysis or GO_analysis.

Examples

res <- spinglass_procedure(fpkm, phe, leading_genes, mppi, 'mouse', n_threads=50)

lanagarmire/NMFEM documentation built on May 20, 2019, 7:34 p.m.