I can't run Ltree if I don't run the function filterdata. Is there any way to sort this issue? All I wish to do is calculate the cell entropy. Thanks.

Hello!

Thank you for the wonderful software. I have a question, is it possible to run STEMID calculations for a Seurat object? I would like to calculate STEMID scores of clusters of cells that have been already calculated and projected using UMAP.

Thank you!

Hi,

I am trying to apply the RaceID/StemID pipeline to my scRNA seq dataset, however, even though I am setting the number of clusters to a specific number with this line sc <- clustexp(sc,cln=10,sat=FALSE), I systematically end up with a higher number of clusters at the end.
How can I manage this ?

Also, I am initially working with a Seurat object, ultimately, I would like to extract the barcodes that show the highest score in StemID and see to which cluster it matches in my Seurat Object.

With "combined" beeing my Seurat object, here is the script used :

`combined_counts <- as.matrix(GetAssayData(combined, slot = "counts"))
combined_meta <- [email protected]

n<-colnames(combined_counts)
b<-list(n[grep("^CON89",n)],n[grep("^CON90",n)])

Create SCseq object for RaceID + batch effect correction

sc <- SCseq(combined_counts)
sc <- filterdata(sc, LBatch=b, bmode="RaceID",mintotal = 1000) # Adjust 'mintotal' based on your data
sc <- compdist(sc, metric = "pearson")
sc <- clustexp(sc)

sc <- clustexp(sc,cln=10,sat=FALSE)

sc <- findoutliers(sc)

plotbackground(sc)
plotsensitivity(sc)

plotoutlierprobs(sc)

clustheatmap(sc)

Run t-SNE

sc <- comptsne(sc)
sc <- compumap(sc)
saveRDS(sc, file="sc_object_final_before_StemID.rds")

Run RaceID and StemID analysis

stem <- Ltree(sc)
stem <- compentropy(stem)
stem <- projcells(stem, cthr = 5, nmode = FALSE)
stem <- projback(stem, pdishuf = 100)
stem <- lineagegraph(stem)

stem <- comppvalue(stem, pthr = 0.05)

Identify stem cell clusters

stemID_scores<- compscore(stem)

There are two instances where sc is used instead of object@sc in projcells
line 889: pdil <- sc@tsne[f,]
line 894: cn <- as.data.frame(pdi[compmedoids(sc@fdata[,names(lp)],lp),])

Dear all,

I am trying to run StemID on my Seurat object on which I have done both the QC needed and the clustering analysis. I am following both the answer here and the tutorial here.

Unfortunately I meet the following error when I perform the comppvalue step.

Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x),  : 
  'data' must be of a vector type, was 'NULL'

Here is all the code I am running:

# Create the sc object
seurat_integrated <- readRDS("file.rds")

ndata <- seurat_integrated@assays$RNA@counts[,]

sc <- SCseq(ndata)

# Filter for this
sc <- filterdata(sc, mintotal = 2000)

# Re-initialize raceID
part <- as.numeric([email protected]$seurat_clusters)
d <- as.matrix(dist(seurat_integrated@[email protected]))
umap <- as.data.frame(seurat_integrated@[email protected])
names(part) <- colnames(d)

n <- colnames(sc@ndata)
part <- part[n]

# partition
sc@cpart <- sc@cluster$kpart <- part
# distances
sc@distances <- d[n,n]
# umap
sc@umap <- umap[n,]
# expression data (optional)
sc@counts <- sc@counts * 0 + 1
sc@ndata  <- ndata[,n]
# cluster medoids
sc@medoids <- compmedoids(sc, sc@cpart)

col_cluster <- colorRampPalette(brewer.pal(12,"Set3"))(length(unique([email protected]$seurat_clusters)))
names(col_cluster) <- as.character(unique([email protected]$seurat_clusters))

set.seed(12345)
sc@fcol <- col_cluster[order(as.numeric(names(col_cluster)))]


# Run StemID

ltr <- Ltree(sc)

ltr <- compentropy(ltr)
ltr <- projcells(ltr,cthr=5,nmode=TRUE,fr=TRUE, um=T, knn=3)

ltr <- lineagegraph(ltr)

ltr <- comppvalue(ltr,pthr=0.05)
# Here I get the error

plotgraph(ltr,showCells=FALSE,showMap=TRUE)

x <- compscore(ltr)

Can anyone help me on this?
I really thank you in advance for this,
Have a great day,
Alessandro

Hi, thank you for developing StemID! I tried to run StemID on my seurat object following the closed issues. However, it errors when I run the code:

 ltr <- projcells(
  object = ltr,
  cthr=5
)
Error in `.rowNamesDF<-`(x, value = value) : invalid 'row.names' length

I will appreciate a lot if you help me! Thank you very much!

Hi, apologies if this might be a naive mistake I'm running into, however, when I run the command projcells(ltr)
I get the error
Error in .local(x, ...) : arguments must have same length
This occurs with the sample data, as well as my own dataset.
Traceback shows:

6.
stop("arguments must have same length") 
5.
.local(x, ...) 
4.
aggregate(pdil, by = list(lp), median) 
3.
aggregate(pdil, by = list(lp), median) at RaceID2_StemID_class.R#890
2.
projcells(ltr) at RaceID2_StemID_class.R#868
1.
projcells(ltr) 

Traceback highlights:

  nrx <- NROW(x)
  if (any(lengths(by) != nrx)) 
    **stop("arguments must have same length")**
  y <- as.data.frame(by, stringsAsFactors = FALSE)
  keep <- complete.cases(by)
  y <- y[keep, , drop = FALSE]
  x <- x[keep, , drop = FALSE]

To be completely honest, I have no idea what this means, being a novice at R and programming in general. Please let me know if I can provide any additional information.

My software versions:
RStudio Version 1.0.136
R version 3.3.2 (2016-10-31)
64bit Win10

Any insight into why this is failing at the beginning of StemID would be much appreciated.
Thanks!

Hi I'm new to RaceID2/StemID

and have a question if I can add additional cell identifier to SCseq object.

such as sample IDs and replicate IDs. are there anyways to store meta.data of the object?

Thank you in advance!