Description Usage Arguments Value References See Also Examples
This function determines which Signatures (GPS) from a collection of GPS data
(GPSrepo
argument) for the specified pathway repository are present in the
specified list of genes of interest (queryList
argument)). It then uses the
distribution function of hypergeometric probabilities to identify the pathways
whose GPS are over-represented among the present GPS and saves the results to
the file specified in the saveFile
argument.
1 2 |
GPSrepo |
An object created by |
level |
In hierarchical repositories (e.g. Reactome) number of levels to consider. Recommended value for KEGG: 2, for Reactome: 4. |
markers |
Whether to take single genes that are uniquely associated with only one pathway into account (i.e. should pathway unique genes/PUGs be considered GPS?). Recommended value: TRUE (1). |
queryList |
A user specified list of genes of interest ('query list'), as a vector of ENSEMBL/ ENTREZ IDs or gene symbols (HGNC/MGI). |
saveFile |
If provided, the results are saved here as a tab delimited File (including , for each pathway, a list of genes ordered by their contribution to the statistical significance of the pathway). |
weighting.method |
The weighting method or GPS. The default weighting scheme for the GPS is the reciproc of the harmonic mean of
the degrees of the two component genes of a GPS. A wide range of alternative
weighting schemes are pre-implemented (see below). Additional user defined
weighting schemes are also supported. Currently, the following alternatives are pre-implemented: |
idmap |
A dataframe for converting between different gene-identifier types (e.g. ENSEMBL, ENTREZ and HGNC-Symbols of genes). Most users do not need to set this argument, as there is a built-in conversion table. |
summary_results |
A dataframe listing the analysis results. |
detailed_results |
A dataframe describing the detailed evidence (present Gene-Pair Signatures) for each pathway. |
Foroushani AB, Brinkman FS and Lynn DJ (2013).“Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures.”PeerJ, 1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## Not run:
##query list
ils<-grep("^IL",idmap[["Symbol"]],value=TRUE)
## using precompiled GPS repositories:
sigRes.ilreact<-sigora(queryList=ils,GPSrepo=reaH,level=4)
sigRes.ilkeg<-sigora(queryList=ils,GPSrepo=kegH,level=2)
## user created GPS repository:
nciH<-makeGPS(pathwayTable=nciTable)
sigRes.ilnci<-sigora(queryList=ils,GPSrepo=nciH,level=2)
## user defined weighting schemes :
myfunc<-function(a,b){1/log(a+b)}
sigora(queryList=ils,GPSrepo=nciH,level=2, weighting.method ="myfunc")
## End(Not run)
|
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