When using monocle for pseudo-timing analysis, an error is reported in the newCellDataSet function.

newCellDataSet(data.matrix(mat_to_cluster), phenoData = pd, featureData = fd, 
                                    expressionFamily = negbinomial.size(),
                                    lowerDetectionLimit = 0.1)

The previous version of R was 4.1 and it could run normally, but when it was upgraded to version 4.2, an error was reported. As shown in the picture above, I tried a variety of methods and finally found that it can be run using Seurat's as.sparse function, that is, data.matrix Replace with as.sparse

newCellDataSet(as.sparse(mat_to_cluster), phenoData = pd, featureData = fd, 
                                    expressionFamily = negbinomial.size(),
                                    lowerDetectionLimit = 0.1)

But I found that the clustering results were different. Before, it was 7 categories.

Now it’s category 13

Because of version issues, the clustering results are also different. I haven’t thought of how to do this for the time being, but it’s not a big problem. We can design how to cluster by ourselves.