DRaWR (version 1.0.3)

DRaWR: DRaWR

Description

This function runs the DRaWR two stage random walk with restart method.

Usage

DRaWR(possetfile = "extdata/sample.setlist", unifile = "extdata/sample.uni",
  networkfile = "extdata/sample.edge", outdir = "output_",
  restarts = c(0.7), nfolds = 1, st2keep = 1, undirected = TRUE,
  unweighted = FALSE, normalize = "type", maxiters = 50, thresh = 1e-04,
  property_types = c("allen_brain_atlas", "chip_binding", "gene_ontology",
  "motif_u5", "pfam_domain", "T1", "T2"), writepreds = 0)

Arguments

possetfile

(string): location of file containing location of gene sets to test.

unifile

(string): location of file listing gene universe.

networkfile

(string): location of file containing network contents.

outdir

(string): prefix of location of file to write performance results (optionally prediction results).

restarts

(vector): vector of restart values to test. Default is c(0.7).

nfolds

(int): number of folds for cross validation, 1 is no cross-validation. Default is 4.

st2keep

(int): number of property nodes to keep in second stage for each property type. Default is 50.

undirected

(bool): boolean to make network undirected.

unweighted

(bool): boolean to make network unweighted.

normalize

(string): "type" or "none". Default is 'type'.

maxiters

(int): maximum number of allowable iterations. Default is 50.

thresh

(float): threshold for L1 norm convergence. Default is 0.001.

property_types

(vector): list of possible property types. Default is c("go_curated_evidence", "go_inferred_evidence", "pfam_domain").

writepreds

(boolean): write predictions out to a file. Default is FALSE

Examples

# NOT RUN {
DRaWR(possetfile = system.file("extdata", "sample.setlist", package="DRaWR"),
	unifile = system.file("extdata", "sample.uni", package="DRaWR"),
	networkfile = system.file("extdata", "sample.edge", package="DRaWR"),
	outdir = "exampleRun_", restarts = c(.7), nfolds = 1, st2keep = 1,
	undirected = TRUE, unweighted = FALSE, normalize = "type", maxiters = 50,
	thresh = 0.0001, property_types = c("T1", "T2"), writepreds = 0)
# }