run_all_metabolites: Runall function to do complete predictions and comparison for...

In borenstein-lab/mimosa2: Model-based Integration of Metabolite Observations and Species Abundances

Runall function to do complete predictions and comparison for all shared metabolites

Description

Runall function to do complete predictions and comparison for all shared metabolites

Usage

run_all_metabolites(
  genes,
  mets,
  file_prefix = "net1",
  correction = "fdr",
  cutoff = 0.1,
  net_method = "load",
  rxn_table_source = "",
  id_met = F,
  met_id_file = "",
  degree_filter = 0,
  minpath_file = "",
  cor_method = "spearman",
  net_file = "",
  nperm = 20000,
  nonzero_filter = 3,
  norm = T,
  save_out = T
)

Arguments

genes	Gene abundances
mets	Metabolite abundances
file_prefix	Prefix for output files
correction	Type of multiple hypothesis correction to perform (bonferroni or fdr)
cutoff	Q/P-value cutoff for significance
net_method	Network generation method (see generate_genomic_network)
id_met	Whether metabolites have putative identifications that need to be processed
met_id_file	If id_met, file of metabolite identifications
degree_filter	Threshold for filtering currency metabolites
minpath_file	Optional file of pathways to filter network to
cor_method	Either "spearman" or "pearson", default is Spearman
net_file	file containing network template to use
nperm	Number of permutations for Mantel test, default is 20000
nonzero_filter	Minimum number of samples required to have nonzero concentrations and nonzero metabolic potential scores in order for metabolite to be evaluated, default is 3
norm	Whether to normalize the network model coefficients by the total number of synthesis and degradation reactions for each metabolite
save_out	Whether to save output

Value

No return, writes output to files.

borenstein-lab/mimosa2 documentation built on Dec. 19, 2024, 12:44 a.m.