StrengthTrainer GLSY22522, User Manual

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the carriage return (i.e. the key labeled “Enter” on the keyboard) should be pressed
immediately after LABEL_END.
Figure 2: An example input expression data file with two sets of labels
b.
Interactome data : The interactome data file is tab-separated and has two columns –
the first column corresponds to hubs and the second column to interactors. The first
row of the data file is assumed to be the header and is ignored while reading the
data. For protein interactomes, the names of hubs and their interactors can be
provided as Entrez IDs or gene symbols but not as a combination of the two. For
microRNA interactomes, the names of interactors can be provided as Entrez IDs or
gene symbols.
Input parameters
We assume that a network module comprises two types of genes – hub and interactor.
The hub gene is connected to all the interactor genes and every interactor gene is
connected to only the hub gene. The main function for identifying the enriched network
modules is
identifySignificantHubs.
This function has 14 input parameters and a detailed
description of the parameters is provided in the PDF file
VAN_Package_Functions.pdf
.
Of the 14 input parameters, only four have to be explicitly specified by the user – exprFile ,
labelIndex , mapFile , and outFile . The default values for the remaining 10 parameters need
to be changed only under certain conditions and below we describe those conditions.
Parameter Condition where the default value should be
changed
hubSize = 5 By default, only those network modules
that have at least 5 interactors in the
expression data set are considered for
downstream analysis. This value can be
changed to consider more dense or sparse
modules.
randomizeCount = 1000 By default 1000 permutations are
performed to determine the p-value. The
user can select a higher number of
permutations, however, it should be noted
Set 1
Set 2