gatingTemplate-class | R Documentation |
Each cell population is stored in graph node and is connected with its parent population or its reference node for boolGate or refGate.
It parses the csv file that specifies the gating scheme for a particular staining pannel.
gatingTemplate(x, ...)
## S4 method for signature 'character'
gatingTemplate(
x,
name = "default",
strict = TRUE,
strip_extra_quotes = FALSE,
...
)
## S4 method for signature 'data.table'
gatingTemplate(
x,
name = "default",
strict = TRUE,
strip_extra_quotes = FALSE,
...
)
x |
|
... |
other arguments passed to |
name |
|
strict |
|
strip_extra_quotes |
|
This csv must have the following columns:
'alias': a name used label the cell population, the path composed by the alias and its precedent nodes (e.g. /root/A/B/alias) has to be uniquely identifiable. So alias can not contain '/' character, which is reserved as path delimiter.
'pop': population patterns of '+/-‘ or ’+/-+/-', which tells the algorithm which side (postive or negative) of 1d gate or which quadrant of 2d gate to be kept.
'parent': the parent population alias, its path has to be uniquely identifiable.
'dims': characters seperated by comma specifying the dimensions(1d or 2d) used for gating. It can be either channel name or stained marker name (or the substrings of channel/marker names as long as they are uniquely identifiable.).
'gating_method': the name of the gating function (e.g. 'flowClust'). It is invoked by a wrapper function that has the identical function name prefixed with a dot.(e.g. '.flowClust')
'gating_args': the named arguments passed to gating function (Note that double quotes are often used as text delimiter by some csv editors. So try to use single quote instead if needed.)
'collapseDataForGating': When TRUE, data is collapsed (within groups if 'groupBy' specified) before gating and the gate is replicated across collapsed samples. When set FALSE (or blank),then 'groupBy' argument is only used by 'preprocessing' and ignored by gating.
'groupBy': If given, samples are split into groups by the unique combinations of study variable (i.e. column names of pData,e.g."PTID:VISITNO"). when split is numeric, then samples are grouped by every N samples
'preprocessing_method': the name of the preprocessing function(e.g. 'prior_flowclust'). It is invoked by a wrapper function that has the identical function name prefixed with a dot.(e.g. '.prior_flowclust') the preprocessing results are then passed to gating wrapper function through 'pps_res' argument.
'preprocessing_args': the named arguments passed to preprocessing function.
## Not run:
gt <- gatingTemplate(system.file("extdata/gating_template/tcell.csv",package = "openCyto"))
plot(gt)
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.