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SigPathway

Performs pathway analysis by computing NEk and NTk statistics described in Tian et al (2005).

The NEk statistic is computed using sample group permutation, so a decent number of samples is necessary. You can study only the NTk statistic by setting the allpathways parameter to TRUE. Currently uses only first ID for genes with multiple comma separated IDs.

More details can be found in the sigPathway R package documentation.

Version 1.0
Bundle microarray
Categories Pathway
Authors Viljami Aittomaki (viljami.aittomaki@helsinki.fi)
Issue tracker View/Report issues
Requires R ; sigPathway (R-bioconductor)
Source files component.xml SigPathway.r
Usage Example with default values

Inputs

Name Type Mandatory Description
expr LogMatrix Mandatory Expression matrix with samples as columns and gene ID's as rows. ID's must be EntrezGene ID's!
samplegroup SampleGroupTable Mandatory SampleGroupTable file containing the sample group (e.g. phenotype) of the columns in expr. All columns of expr do not have to be present in the table. Those columns that are not present are ignored. Multiple groups are allowed. The Type and Description columns are ignored.

Outputs

Name Type Description
pathways CSV Highly ranking pathways according to the statistics used by sigPathway. Contains columns 'Gene Set Category', 'Pathway', 'Set Size', 'Percent Up', 'NTk Stat', 'NTk q-value', 'NTk Rank', 'NEk Stat', 'NEk q-value', 'NEk Rank' and 'Probes'.

Parameters

Name Type Default Description
allpathways boolean false Indicates whether to include all pathways or just the top npath pathways (sorted by the sum of ranks of both statistics) in the result table. If false, only consistently high ranking pathways are considered. If true, the resulting pathway table can be very long.
alwaysRandPerm boolean false Indicates whether the algorithm will use random permutations even when nsim is greater than the total number of unique permutations possible with the number of samples and their groups (or phenotypes). If false, complete permutation is used in such cases.
maxNPS int 500 Maximum number of probe sets a pathway can contain to be included in the analysis.
minNPS int 20 Minimum number of probe sets a pathway must contain to be included in the analysis.
npath int 25 Number of top gene sets to consider from each statistic when ranking the top pathways.
nsim int 1000 Number of permutations used for computing null-distribution.
seed int 0 Seed for random number generator (for permutations). Use a nonzero value (zero is the default value for not setting the seed manually).
weightType string "constant" Type of weight to use when calculating NEk statistics, 'constant' or 'variable'. Constant is faster. However, if the histogram of unadjusted p-values (for the genes from a t-test-like hypothesis test) is nearly horizontal, and the top ranked pathways have high NEk q-values (i.e. approaching 1), setting weightType to 'variable' should help lower some of the NEk q-values.

Test cases

Test case Parameters IN
expr
IN
samplegroup
OUT
pathways
case1 (missing) expr samplegroup (expecting failure)
case2 properties expr samplegroup pathways

minNPS=3,
maxNPS=250,
nsim=300,
seed=666


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