phantom (version 0.1.3)

run.phantom.batch: Run phantom batch analysis

Description

This function allows user to run batch analysis of a full geneset list with phantom, and download the identified heterogeneous genesets

Usage

run.phantom.batch(data = NULL, geneset_list = NULL, maxncluster = 5,
  nsample = 1000, report_pval = 0.05, report_nmin = 5,
  output_dir = file.path("./phantom_result"))

Arguments

data

User provided time-course data loaded by load.data()

geneset_list

User provided genesets list loaded by load.geneset(). Phanotm package provids four geneset lists from different resources: kegg, reactome, emory geneset and baylor modules. These genesets can be obtained with data(), e.g. data(kegg.geneset)

maxncluster

The maximum number of clusters within a geneset user wants to test with. All numbers from 1 to ncluster will be tested and an optimal cluster number will be selected to identify the heterogeneity of this geneset.

nsample

The times of random sampling that is used to build the NULL distribution for parato front analysis.

report_pval

The maximum p value of a geneset that will be reported as a significant heterogeneous geneset. Genesets with p value larger than report_pval wil not be reported

report_nmin

The minmum size of subcluster in a geneset that will be reported as a significant heterogeneous geneset.

output_dir

The directory where user wants to put the phantom batch analysis results

Examples

# NOT RUN {
## load in the demo data and geneset in phantom package
data("time.course.data")
data("kegg.geneset")

## store the analysis result in an object
# }
# NOT RUN {
obj = run.phantom.batch(data = time.course.data, geneset_list = kegg.geneset,
                  maxncluster = 5, nsample = 1000, report_pval = 0.05, report_nmin = 5,
                  output_dir = file.path(getwd(),'/phantom_result'))
# }