How to merg/standardize GatingSets ======================================================== Usage ------------------------------------------------------ ```{r eval=FALSE} groupByTree(x) checkRedundantNodes(x) dropRedundantNodes(x,toRemove) dropRedundantChannels(gs, ...) ``` Arguments ------------------------------------------------------ **x** '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 ```{r echo=FALSE, message=FALSE, results='hide'} library(flowWorkspace) flowDataPath <- system.file("extdata", package = "flowWorkspaceData") gs <- load_gs(file.path(flowDataPath,"gs_manual")) gs1 <- clone(gs) sampleNames(gs1) <- "1.fcs" # simply the tree nodes <- getNodes(gs1) for(toRm in nodes[grepl("CCR", nodes)]) Rm(toRm, gs1) # remove two terminal nodes gs2 <- clone(gs1) sampleNames(gs2) <- "2.fcs" Rm("DPT", gs2) Rm("DNT", gs2) # remove singlets gate gs3 <- clone(gs2) Rm("singlets", gs3) add(gs3, getGate(gs2, "CD3+"), parent = "not debris") for(tsub in c("CD4", "CD8")) { add(gs3, getGate(gs2, tsub), parent = "CD3+") for(toAdd in getChildren(gs2, tsub)) { thisParent <- getParent(gs2[[1]], toAdd, path = "auto") add(gs3, getGate(gs2, toAdd), parent = thisParent) } } sampleNames(gs3) <- "3.fcs" # spin the branch to make it isomorphic gs4 <- clone(gs3) # rm cd4 branch first Rm("CD4", gs4) # add it back add(gs4, getGate(gs3, "CD4"), parent = "CD3+") # add all the chilren back for(toAdd in getChildren(gs3, "CD4")) { thisParent <- getParent(gs3[[1]], toAdd) add(gs4, getGate(gs3, toAdd), parent = thisParent) } sampleNames(gs4) <- "4.fcs" gs5 <- clone(gs4) # add another redundant node add(gs5, getGate(gs, "CD4/CCR7+ 45RA+")[[1]], parent = "CD4") add(gs5, getGate(gs, "CD4/CCR7+ 45RA-")[[1]], parent = "CD4") sampleNames(gs5) <- "5.fcs" library(knitr) opts_chunk$set(fig.show = 'hold', fig.width = 4, fig.height = 4, results= 'asis') ``` ## Remove the redudant leaf/terminal nodes ```{r echo=FALSE} plot(gs1) plot(gs2) ``` Leaf nodes **DNT** and **DPT** are redudant for the analysis and should be **removed** before merging. ## Hide the non-leaf nodes ```{r echo=FALSE} plot(gs2) plot(gs3) ``` **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. ```{r} 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**. ```{r results='hold'} getNodes(gs2)[5] getNodes(gs3)[5] ``` ```{r results='hold'} getNodes(gs2, path = "auto")[5] getNodes(gs3, path = "auto")[5] ``` ## Isomorphism ```{r echo=FALSE} #restore gs2 invisible(setNode(gs2, "singlets", TRUE)) ``` ```{r echo=FALSE} plot(gs3) plot(gs4) ``` 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` ## convenient wrapper for merging To ease the process of merging large number of batches of experiments, here is some **internal wrappers** to make it **semi-automated**. ### Grouping by tree structures ```{r} gslist <- list(gs1, gs2, gs3, gs4, gs5) gs_groups <- groupByTree(gslist) length(gs_groups) ``` This divides all the `GatingSet`s into different groups, each group shares the same tree structure. Here we have `4` groups, ## Check if the discrepancy can be resolved by dropping leaf nodes ```{r error=TRUE} res <- try(checkRedundantNodes(gs_groups), silent = TRUE) print(res[[1]]) ``` 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. ```{r} for(gp in gs_groups) plot(gp[[1]]) ``` Based on the tree structure of each group (usually there aren't as many groups as `GatingSet` objects itself), we will hide `singlets` for `group 2` and `group 4`. ```{r} for(i in c(2,4)) for(gs in gs_groups[[i]]) invisible(setNode(gs, "singlets", FALSE)) ``` Now check again with `.checkRedundantNodes` ```{r} toRm <- checkRedundantNodes(gs_groups) toRm ``` Based on this, these groups can be consolidated by dropping * `CCR7+ 45RA+` and `CCR7+ 45RA-` from `group 1`. * `DNT` and `DPT` from `group 2`. To proceed the deletion of these nodes, `.dropRedundantNodes` can be used instead of doing it manually ```{r results='hide'} dropRedundantNodes(gs_groups, toRm) ``` Now they can be merged into a single `GatingSetList`. ```{r} GatingSetList(gslist) ``` Remove the redundant channels from `GatingSet` ------------------------------------------------------ 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. ```{r} dropRedundantChannels(gs1) ```