Matrix upgrading to the latest version or lowering the version does not solve the error.

[INFJ-A]

The questions are as follows：

Problems encountered with low matrix package versions are as follows：

Error in isTRUE(r <- .Call(Dim_validate, object, "Matrix")) : 
  object 'Dim_validate' not found

The following problems were encountered after the matrix package version was updated

> mmu_go_analyzed = analyzeGOSeurat(go_seurat_obj = mmu_go_obj, cell_type_col = 'cell_type_annotation', min.dist = 0.1, spread = 0.5)
perform normalization and log1p for mmu_go_obj
Warning: The following arguments are not used: spread
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Warning: The following arguments are not used: spread
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Warning: The following arguments are not used: spread
Warning: The following arguments are not used: spread
Warning: The following arguments are not used: spread
Computing nearest neighbor graph
Computing SNN
Warning: The following arguments are not used: spread
Warning: The following arguments are not used: spread
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 219
Number of edges: 9890

Running Louvain algorithm...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Maximum modularity in 10 random starts: 0.4728
Number of communities: 4
Elapsed time: 0 seconds
Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session
17:50:39 UMAP embedding parameters a = 5.069 b = 1.003
17:50:39 Read 219 rows and found 50 numeric columns
17:50:39 Using Annoy for neighbor search, n_neighbors = 30
17:50:39 Building Annoy index with metric = cosine, n_trees = 50
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
17:50:39 Writing NN index file to temp file /tmp/Rtmpow08s1/file3bc71a074a0f
17:50:39 Searching Annoy index using 1 thread, search_k = 3000
17:50:39 Annoy recall = 100%
17:50:40 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
17:50:41 Initializing from normalized Laplacian + noise (using irlba)
Error in irlba::irlba(L, nv = n, nu = 0, maxit = iters) : 
  function 'as_cholmod_sparse' not provided by package 'Matrix'
Attaching SeuratObject

Can anyone help me with this? Thank you for your help.

[YY-SONG0718]

Hello! I think it is a version compatibility problem between Seurat and Matrix. Are you using Seurat V5.0? Perhaps you could remove the Seurat and Matrix packages, then install SeuratV5.0 with dependencies.

[YY-SONG0718]

Matrix_1.6-5 is what I use