groupByTree(x) checkRedundantNodes(x) dropRedundantNodes(x,toRemove) dropRedundantChannels(gs, ...)
'GatingSet' objects or or list of groups (each group member is a list of 'GatingSet)
toRemove list of the node sets to be removed. its length must equals to the length of argument x
… other arguments
Leaf nodes DNT and DPT are redudant for the analysis and should be removed before merging.
singlets node is not present in the second tree. But we can't remove it because it will remove all its descendants. We can hide it instead.
invisible(setNode(gs2, "singlets", FALSE)) plot(gs2) plot(gs3)
Note that even gating trees look the same but singlets still physically exists so
we must refer the populations by relative path (
path = "auto") instead of full path.
##  "/not debris/singlets/CD3+/CD4/38- DR+" ##  "/not debris/CD3+/CD4/38- DR+"
getNodes(gs2, path = "auto") getNodes(gs3, path = "auto")
##  "CD4/38- DR+" ##  "CD4/38- DR+"
These two trees are not identical due to the different order of CD4 and CD8. However they are still mergable thanks to the reference by gating path instead of
by numeric indices
To ease the process of merging large number of batches of experiments, here is some internal wrappers to make it semi-automated.
gslist <- list(gs1, gs2, gs3, gs4, gs5) gs_groups <- groupByTree(gslist)
## Grouping by Gating tree...
This divides all the
GatingSets into different groups, each group shares the same tree structure. Here we have
res <- try(checkRedundantNodes(gs_groups), silent = TRUE) print(res[])
 “Error in (function (thisNodeSet, thisObj) : \n Can't drop the non-terminal nodes: singlets\n”
Apparently the non-leaf node (
singlets) fails this check, and it is up to user to decide whether to hide this node or keep this group separate from further merging.Here we try to hide it.
for(gp in gs_groups) plot(gp[])
Based on the tree structure of each group (usually there aren't as many groups as
GatingSet objects itself), we will hide
group 2 and
for(i in c(2,4)) for(gs in gs_groups[[i]]) invisible(setNode(gs, "singlets", FALSE))
Now check again with
toRm <- checkRedundantNodes(gs_groups) toRm
[]  “CCR7+ 45RA+” “CCR7+ 45RA-”
[]  “DNT” “DPT”
Based on this, these groups can be consolidated by dropping
Sometime it could be difficult to inspect and distinguish tree difference by simply plotting the enire gating tree or looking at this simple flat list of nodes (especially when the entire subtree is missing from cerntain groups). It is helpful to visualize and highlight only the tree hierarchy difference with the helper function
To proceed the deletion of these nodes,
.dropRedundantNodes can be used instead of doing it manually
## Removing CCR7+ 45RA+
## Removing CCR7+ 45RA-
## Removing DNT
## Removing DPT
Now they can be merged into a single
An GatingSetList with 5 GatingSet containing 5 unique samples.
Sometime there may be the extra
channels in one data set that prevents it from being merged with other. If these channels are not used by any gates, then they can be safely removed.
## drop FSC-H, FSC-W, <G560-A>, <G780-A>, Time
A GatingSet with 1 samples