Description Usage Arguments Details Value Examples
RNAMagnet comes in two flavors: RNAMagnetAnchors
and RNAMagnetSignaling
. This function is meant to identify, for each single cell from a seurat
object, the propensity to physically adhere to a set of anchor populations. For example, this function can identify if a single cell is more likely to bind to arteriolar or sinusoidal vessels.
1 2 3 4 5 | RNAMagnetAnchors(seurat, anchors, return = "summary",
neighborhood.distance = 0.7, neighborhood.gradient = 3, .k = 10,
.x0 = 0.5, .minExpression = 0, .version = "latest",
.cellularCompartment = c("Membrane", "ECM", "Both"),
.manualAnnotation = "Correct")
|
seurat |
An object of class |
anchors |
A character vector of anchor populations. Entries must be levels of |
return |
Determines object to return; one of "summary" or "rnamagnet-class" |
neighborhood.distance |
See detail |
neighborhood.gradient |
See detail |
... |
For explanation of all further parameters, see |
Highly similar cell types can localize to different physical structures. For example, one type of pericyte may localize to sinusoids and another type may localize to arterioles. To increase the resolution in this scenario, RNAMagnetAnchors
for each pair of single cells and anchor populations therefore computes a specificity score that describes how the single cell differs from similar cells.
In our hands, the behavior of RNAMagnet is largely insensitive to the parameters neighborhood.distance
and neighborhood.gradient
that define what actually constitutes a similar cell. To explore how these parameters affect the weight each single cell carries in specificity score computation, see the example code.
Returns a data frame containing, for each cell, the propensity to physically interact with the various anchor populations as well as an overall adhesiveness score and prefered interaction partner. Alternatively, if return
ist set to rnamagnet-class
, an object of class rnamagnet
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ## Not run:
result <- RNAMagnetAnchors(NicheData10x, anchors = c("Sinusoidal ECs","Arteriolar ECs","Smooth muscle","Osteoblasts"))
qplot(x =NicheData10x@dr$tsne@cell.embeddings[,1], y=NicheData10x@dr$tsne@cell.embeddings[,2], \
color = direction,size=I(0.75),alpha= adhesiveness,data=result) + \
scale_color_brewer(name = "RNAMagnet\nLocation",palette= "Set1") + \
scale_alpha_continuous(name = "RNAMagnet\nAdhesiveness")
#To understand the effect of the neighborhood.distance and neighborhood.gradient parameters
#consider the following snippet:
myMagnet <- RNAMagnetAnchors(NicheData10x, return = "rnamagnet-class", \
anchors = c("Sinusoidal ECs","Arteriolar ECs","Smooth muscle","Osteoblasts"))
use <- 1234 #select some cell of interest
kernel <- function(x,k=10, x0=0.5) 1/(1+exp(-k * (x-x0))) #defines weighing function
plf <- data.frame(x = seurat@dr$tsne@cell.embeddings[,1],y = seurat@dr$tsne@cell.embeddings[,2], \
weight = 1-kernel(dbig[use,],k=neighborhood.gradient,x0=neighborhood.distance))
qplot(x = x, y= y, color = scores, data=plf) + \
scale_color_gradientn(name = "Weight in local neighborhood", colours = c("#EEEEEE","#999999","blue","red")) + \
geom_point(color = "black", shape = 17, size= 3, data=plf[use,])
## End(Not run)
|
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