Input and Output

Assay Data

Input data containing an expression matrix or matrix-like data structure, with genes as rows and samples as columns. Accepts only CSV and TXT as extension.

Gene Set

Gene set can be taken from 3 categories kegg, Go and Custom gene set uploaded using a txt or csv file containing the name list each element contains a gene set that is a character vector of gene IDs or symbols

Kegg

• Sinaling : sig.idx
• Metabolic : met.idx
• Sigmet : sigmet.idx
• disease : dise.idx
• all : c(sigmet.idx,dise.idx)

GO

• BP : GSETS.BP
• CC : GSETS.CC
• MF : GSETS.MF
• all : BP+CC+MF

If Gene set is chosen as custom a file upload is shown user have to upload the file for the custom gene set 'Species' value is set to custom and 'Gene Id Type' is also set to custom

Gene ID Type

ID type used for the Gene Data. This can be selected from the drop down list. for GO Gene sets the list is restricted to the Gene ID paired with species and auto changes with species value If you are giving the custom gene set Id's then the values is set to custom.

Species

Either the KEGG code, scientific name or the common name of the target species.This can be selected from the autosuggest drop down list.

Control/Reference

Column numbers for the reference condition or phenotype i.e. control group if you specify null than all the columns are considered as target experiments.

Case / Sample

Column numbers for the target condition or phenotype i.e. experiment group in the exprs data matrix. if you specify null than all the columns other than ref are considered as target experiments

Analysis

q-value Cutoff

numeric, q-value cutoff between 0 and 1 for signficant gene sets selection. De- fault to be 0.1.

Set Size

Gene set size (number of genes) range to be considered for enrichment test. Tests for too small or too big gene sets are not robust statistically or informative bio- logically.

Compare

Comparison scheme to be used. List of comparison methods available

• paired: default reference and sample columns should be of equal number of columns
• unpaired: one on one comparison between reference and sample columns
• 1 on Group: one sample column at a time vs the average of the refernce columns
• as group: Used for PAGE-like analysis

Two-direction Test

To test for changes changes towards both directions simultaneously. or test a gene set toward a single direction(all genes up or down regulated)

Rank Test

whether do the optional rank based two-sample t-test (equiv- alent to the non-parametric Wilcoxon Mann-Whitney test) instead of parametric two-sample t-test. This argument should be used with respect to argument Test

Per Gene Score

Whether to use fold changes or t-test statistics as per gene statistics.

Gene Set Test

Function used for gene set tests for single array based analysis. Default to be t-Test, which features a two-sample t-test for differential expression of gene sets. Other options includes:

• z-Test: using one-sample z-test as in PAGE
• Kolmogorov–Smirnov test: using the non-parametric Kolmogorov-Smirnov tests as in GSEA

gs.zTest or Kolmogorov–Smirnov test should only be used when rank.test is set to false

Use Pathview

Argument to perform pathview generation or not.

Data Type

Data type Gene,Compound while generating the pathviews. This argument is visible only when use pathview option is made to true.

Example 1: GAGE Analysis for Pathview

Output Plots and heatmap snapshots:

Individual Heat Map

Individual Scatter Plot

Example 2: GAGE Analysis With Custom Gene Set ID's and Gene ID's

Output Plots and heatmap snapshots:

Individual Heat Map

Individual Scatter Plot