hylasd/tspace

tspace's Issues

Cluster setup failed. 2 of 2 workers failed to connect.

hi, I am going to build a ts file from a matrix. It has 7274 cells with 22457 genes. It is running in rstudio server with 8 CPU and 64G RAM.
Code:
library(tSpace)
Idents(scRNA) <- "orig.ident"
df <- subset(scRNA, idents = 'day5')
df <- GetAssayData(df,slot="data",assay="RNA")
ts <- tSpace(df = df,
K = 20, L = 15,
D = 'pearson_correlation',
graph = 5,
trajectories = 200,
wp = 15, dr = 'pca', core_no = 2)
It shown error like below:
Step 1:Finding graphError in makePSOCKcluster(names = spec, ...) : Cluster setup failed. 2 of 2 workers failed to connect.
In addition: Warning messages: 1: In system(cmd, wait = FALSE) : system call failed: Cannot allocate memory 2: In system(cmd, wait = FALSE) : error in running command Error in save(list = names(.GlobalEnv), file = outfile, version = version, : error writing to connection Error saving session (search_path): R code execution error Error in system(paste(which, shQuote(names[i])), intern = TRUE, ignore.stderr = TRUE) : cannot popen '/usr/bin/which 'pdflatex' 2>/dev/null', probable reason 'Cannot allocate memory' Error in system(paste(which, shQuote(names[i])), intern = TRUE, ignore.stderr = TRUE) : cannot popen '/usr/bin/which 'pdflatex' 2>/dev/null', probable reason 'Cannot allocate memory'

Hope some one would give me some suggestion!
Best!

How to convert seurat object to ts file?

hi team, I try to build a ts file by
ts <- tSpace(df = your_data, K = 20, L = 15, D = 'pearson_correlation', graph = 5, trajectories = 200, wp = 15, dr = 'pca', core_no = 2)
However, how to create the "your_data" from a seurat object? I try the following two ways:

1. data.table<- as.matrix(GetAssayData(seurat_object, slot = "data"))

ts <- tSpace(df = data.table,

•          K = 20, L = 15, 
  

•          D = 'pearson_correlation', 
  

•          graph = 5, 
  

•          trajectories = 200, 
  

•          wp = 15, dr = 'pca', core_no = 8)
  

Step 1:Finding graphError in graph.adjacency.sparse(adjmatrix, mode = mode, weighted = weighted, :
not a square matrix

2. data.table<- as.matrix(GetAssayData(seurat_object, slot = "data"))
   data.table <- as(data.table, 'sparseMatrix')

ts <- tSpace(df = data.table,

•          K = 20, L = 15, 
  

•          D = 'pearson_correlation', 
  

•          graph = 5, 
  

•          trajectories = 200, 
  

•          wp = 15, dr = 'pca', core_no = 8)
  

Step 1:Finding graphError in { :
task 1 failed - "unable to find an inherited method for function ‘[’ for signature ‘"dgCMatrix"’"

How to create an eligible "your_data" file? Thanks a lot!

Running tSPACE on large datasets. Issues with igraph: Weight vector must be non-negative

Hi,

Thanks a lot for your great work. I'm trying to run tSpace on a dataset of 200'000 cells x 15 PCs (on Mac iOS). However I get the following error [Error in { :
task 1 failed - "At structural_properties.c:4295 : Weight vector must be non-negative, Invalid value"], which I believe is a problem with the igraph dependency. When I run tSpace on a downsample of the dataset (2'000 cells x 15 PCs), I'm able to obtain my ts_file. I tried to install previous version of igraph (1.1.2) as suggested, but I still get the same error. Thank you very much!

Integration tSpace and seurat object

Hi,

Do you know how to upload data from seurat object to tSpace and also save the same plot (based in UMAP embeddings from seurat)?

issue about calculation in tSPACE

Hi Denis,

Thanks for the beautiful tool tSPACE, I have been trying to use it to build reasonable trajectories for a bunch of developmental single cell data.
Here I have got some issue:

  I first ran a small dataset with about 3k cells and 1.5k variable genes, it took 15h to run on a 64G local PC, the trajectory output seems pretty good.

  then I wanted to run a bigger one with about tens of thosands of cells and same parameters, but it was terminated by me after 100h without an end.

  then I chose to use the top PCs as input, though it could be completed in just a few hours, the tSPACE output result becomes very similar to my old UMAP calculated using the same PCs. It seems like the existing PCs have been determined a lot by custom pre-normalization/-integration. Additionally, if a few datasets have to run individually, it might be hard to keep the consistensy.

So my question is: if there is a way to extract the tPC formula, as getting PCA coefficient from seur.obj@reductions$[email protected] ?
Then I could run tSPACE on a standard and relatively small dataset at first, then extract the formula for each tPC, after that, I could do the calculation using those pre-built tPC-formulas on any new and bigger datasets with similar celltypes and same pre-normalization.

Kind Wishes,

Shaorui

Installation (mac) and R version 3.6.

Hi,

I have a problem wit installing tSpace.

Error: (converted from warning) package ‘foreach’ was built under R version 3.6.2
Execution halted
ERROR: lazy loading failed for package ‘tSpace’

• removing ‘/Library/Frameworks/R.framework/Versions/3.6/Resources/library/tSpace’
  Error: Failed to install 'tSpace' from GitHub:
  (converted from warning) installation of package ‘/var/folders/46/yxc2wz6n091738r0rv_55jm40000gn/T//RtmpqiW6AZ/file1069849dc0658/tSpace_0.1.0.tar.gz’ had non-zero exit status

Can you help me with that?

Error in the graphfinder function

Thank you for the great work. I was trying to run tSpace on my dataset - 50 PCs of around 11000 cells. However, tSpace failed with error '"Error in -rem : invalid argument to unary operator"'. I debugged and traced the error to line 64 of the graphfinder function

tSpace/R/helper_functions.R

Line 98 in 0c85e13

temp <- temp[-rem,]

Turns out in my case 'rem' list is empty - it just contains 50 NULL objects. Because of this empty list the step mentioned above fails. The 'rem' object is created a few lines before in a parallel process I cannot debug further, so I'm not sure which line exactly is causing the problem.

Could you please assist me in solving this issue?