faster logmap labels

[mihem]

Issue initially reported here:
satijalab/seurat#7879

Integration preprocessing took long (~10min in my case with 120 000 cells and 61 layers). Time was nearly completely spent on Seurat:::CreateIntegrationGroup , more specifically on:

    as.data.frame(x = labels(
      object = cmap,
      values = Cells(x = object[[assay]], layer = scale.layer)

Slow computing here was caused by the sapply function in seurat-object

seurat-object/R/logmap.R

Lines 238 to 247 in 58bf437

	obs <- sapply(
	X = values,
	FUN = function(x) {
	vals <- colnames(x = object)[which(x = object[x, , drop = TRUE])]
	p()
	return(vals)
	},
	simplify = FALSE,
	USE.NAMES = TRUE
	)

I rewrote this (also thanks to ChatGPT) using logical indexing.
This speeds up computation > 1000x in my use case from 10 min to less than 1 s. So "real" integration steps start nearly instantaneously.

For a reproducible example use:

library(Seurat)
library(SeuratData)
options(future.globals.maxSize = 1e9)

remotes::install_github("mihem/seurat-object@faster_logmap")

InstallData("pbmcsca")
obj <- LoadData("pbmcsca")

obj[["RNA"]] <- split(obj[["RNA"]], f = obj$Method)

obj <- NormalizeData(obj)
obj <- FindVariableFeatures(obj)
obj <- ScaleData(obj)

layers <- Layers(object = obj, assay = "RNA", search = "data")
scale.layer <- Layers(object = obj, search = "scale.data")

system.time(
    groups <- Seurat:::CreateIntegrationGroups(obj[["RNA"]], layers = layers, scale.layer = scale.layer)
)

[mihem]

@Gesmira or @dcollins15
Would be nice if you could review that,. simple changes but enormous speedup.

[mihem]

An news here? already some weeks old @Gesmira @igrabski?