This is a fork from PMBio's MuDataSeurat

Please refer to the original repo for more details

I find MuDataSeurat to be the most compatible tool for converting SeuratObject to H5AD/H5MU format. It does not require python runtime as well.

The original repository activity seems quite low, and unfortunately, the bugs have not been fixed promptly. Since I use MuDataSeruat quite often, I've decided to create my own fork and make my own version. I will do my best to ensure that it remains compatible with the latest pull requests from the original repository.

1. Compatible with Seurat v5
2. Tested and works with anndata (>=0.8), and anndata-rs(>=0.2.0).
3. Export all missing reductions, such as UMAP, tSNE etc.
4. Fixed stack overflow issue because of obs column containing NAs
   • skip columns with all NA value
   • fixed string array with NA
5. Add two new keyword arguments to WriteH5AD and WriteH5MU:
   • scale.data: whether write scale.data to anndata/mudata or not.
   • sparse.type: store csc_matrix or csr_matrix in anndata/mudata

Please install the main branch

remotes::install_github("zqfang/MuDataSeurat")

MuDataSeurat only export 3 layers: count, data, scale.data

Therefore, You need JoinLayers for each modality first with seurat v5.

library(MuDataSeurat)

DefaultAssay(seu) = "RNA"
seu = JoinLayers(seu) # critical for seurat v5

## write unimodal h5ad
WriteH5AD(seu, "export.h5ad",  assay="RNA", scale.data = FALSE, overwrite=TRUE)

## write multimodal h5mu
WriteH5MU(seu, "export.h5mu", overwrite=TRUE)

ReadH5AD()
ReadH5MU()

You may also use the native support of anndata in R: anndataR::read_h5ad