tna.get {RTN} | R Documentation |
Get information from individual slots in a TNA object. Available results from a previous analysis can be selected either by pvalue cutoff (default) or top significance.
tna.get(object, what="summary", order=TRUE, ntop=NULL, reportNames=TRUE, idkey=NULL)
object |
an object of class |
what |
a single character value specifying which information should be retrieved from the slots. Options: 'summary', 'status', 'para', 'pheno', 'hits', 'regulatoryElements', 'tnet', 'refnet', 'regulons', 'refregulons', 'regulons.and.mode', 'refregulons.and.mode', 'rowAnnotation', 'colAnnotation', 'mra', 'gsea1', 'gsea2', 'overlap', 'synergy', 'shadow'. |
order |
a single logical value specifying whether or not the output data should be ordered by significance. Valid only for 'gsea1', 'gsea2', 'overlap', 'synergy' or 'shadow' options. |
ntop |
a single integer value specifying to select how many results of top significance from 'gsea', 'overlap', 'synergy' or 'shadow' options. |
reportNames |
a single logical value specifying to report regulons with 'names' (when reportNames=TRUE) or not (when reportNames=FALSE). This option is effective only if transcription factors were named with alternative identifiers in the pre-processing analysis. It takes effect on 'mra', 'gsea', 'overlap', 'synergy' and 'shadow' options. |
idkey |
an optional single character value specifying an ID name from the available 'TNA' annotation to be used as alias for data query outputs (obs. it has no effect on consolidated tables). |
Options for the 'what' argument retrieve the following types of information:
A list summarizing parameters and results available in the TNA object.
A vector indicating the status of each available method in the pipeline.
A list with the parameters used by each available method in the pipeline.
A numeric vector of phenotypes named by gene identifiers (see tni2tna.preprocess
).
A character vector of gene identifiers for those considered as hits (see tni2tna.preprocess
).
A vector of regulatory elements (e.g. transcription factors).
A data matrix with MI values, evaluated by the DPI filter. MI values are computed between regulators and targets, with regulators on cols and targets on rows. Note that signals (+/-) are assigned to the inferred associations in order to represent the 'mode of action', which is derived from Pearson's correlation between regulators and targets.
A data matrix with MI values (not evaluated by the DPI filter). MI values are computed between regulators and targets, with regulators on cols and targets on rows. Note that signals (+/-) are assigned to the inferred associations in order to represent the 'mode of action', which is derived from Pearson's correlation between regulators and targets.
A list with regulons extracted from the 'tnet' data matrix.
A list with regulons extracted from the 'refnet' data matrix.
A list with regulons extracted from the 'tnet' data matrix, including the assiged 'mode of action'.
A list with regulons extracted from the 'refnet' data matrix, including the assiged 'mode of action'.
A data frame with probe-to-gene annotation.
A data frame with sample annotation.
A data frame with results from the tna.mra
analysis pipeline.
A data frame with results from the tna.gsea1
analysis pipeline.
A data frame with results from the tna.gsea2
analysis pipeline.
A data frame with results from the tna.overlap
analysis pipeline.
A data frame with results from the tna.synergy
analysis pipeline.
A data frame with results from the tna.shadow
analysis pipeline.
Get the slot content from a TNA-class
object.
Mauro Castro
data(tniData) data(tnaData) ## Not run: rtni <- tni.constructor(expData=tniData$expData, regulatoryElements=c("PTTG1","E2F2","FOXM1","E2F3","RUNX2"), rowAnnotation=tniData$rowAnnotation) rtni <- tni.permutation(rtni) rtni <- tni.bootstrap(rtni) rtni <- tni.dpi.filter(rtni) rtna <- tni2tna.preprocess(rtni, phenotype=tnaData$phenotype, hits=tnaData$hits, phenoIDs=tnaData$phenoIDs) # run MRA analysis pipeline rtna <- tna.mra(rtna) # check summary tna.get(rtna,what="summary") # get results, e.g., from the MRA analysis tna.get(rtna,what="mra") ## End(Not run)