NetMoss: Identifying Differential Bacteria Based on a Network...

View source: R/NetMoss.R

NetMossR Documentation

Identifying Differential Bacteria Based on a Network Workflow.

Description

This is a function to identify differential bacteria between case and control data set.

Usage

NetMoss(
  case_dir,
  control_dir,
  net_case_dir,
  net_control_dir,
  deepSplit = 4,
  minModuleSize = 20
)

Arguments

case_dir

string.The directory of diseased data set.

control_dir

string.The directory of healthy data set.

net_case_dir

string.The directory of network correlation of diseased data set.

net_control_dir

string.The directory of network correlation of healthy data set.

deepSplit

For method "hybrid", can be either logical or integer in the range 0 to 4. For method "tree", must be logical. In both cases, provides a rough control over sensitivity to cluster splitting. The higher the value (or if TRUE), the more and smaller clusters will be produced. For the "hybrid" method, a finer control can be achieved via maxCoreScatter and minGap below.

minModuleSize

Minimum module size.

Value

NetMoss score and module division results of each bacterium.

Examples

case_dir = '/tests/case_dir'
control_dir = '/tests/control_dir'
net_case_dir = '/tests/net_case_dir'
net_control_dir = '/tests/net_control_dir'
NetMoss(case_dir = case_dir,
     control_dir = control_dir,
     net_case_dir = net_case_dir,
     net_control_dir = net_control_dir)


xiaolw95/NetMoss documentation built on May 8, 2022, 11:03 p.m.