View source: R/sparrow_integration.R
ct.seasPrep | R Documentation |
Take in a list of results objects and return an equivalently-named list of input 'data.frames' appropriate for 'sparrow::seas()'. By construction, the relevant target unit is extracted from the 'geneSymbol' column of the provided results objects, which may. Note that the genewise '@logFC' slot in the returned object will contain the appropriately-signed Z transformation of the P-value assigned to the target. In most applications this is arguably more interpretable than e.g., the median gRNA log2 fold change.
ct.seasPrep( dflist, collapse.on = c("geneID", "geneSymbol"), cutoff = 0.1, statistic = c("best.q", "best.p"), regularize = FALSE, gdb = NULL, active = "replicated" )
dflist |
A list of gCrisprTools results 'data.frames' to be formatted. |
collapse.on |
Should targets be annotated as 'geneSymbol's or 'geneID's (default)? |
cutoff |
Numeric maximum value of 'statistic' to define significance. |
statistic |
Should cutoffs be calculated based on FDR ('best.q') or P-value ('best.p')? |
regularize |
Logical indicating whether to regularize the result objects in 'dflist' (e.g., use intersection set of all targets), or keep as-is. |
gdb |
Optionally, a 'GeneSetDb' object to enable proper registration of the output. If provided, the collapsing features in the provided 'simpleDF's must be present in the 'gsd@db$feature_id' slot. Note that a GREAT-style 'GeneSetDb' that has been conformed via 'ct.GREATdb()' will use 'geneID's as the 'feature_id'. |
active |
Optionally, the name of a logical column present in the provided result that will be used to define significant signals. This is set to 'replicated' by default to If a valid column name is provided, this overrides the specification of 'cutoff' and 'statistic'. |
A list of 'data.frames' formatted for evaluation with 'sparrow::seas()'.
data(resultsDF) ct.seasPrep(list('longer' = resultsDF, 'shorter' = resultsDF[1:10000,]), collapse.on = 'geneSymbol')
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