Add support for Seurat v4 objects

[rainbowkiva]

I tried to convert the rds data from Seurat v4 to h5ad data, but I encountered an error when running the following code:

Seurat v4 lacks a “layers” structure, which has left me perplexed. Is there an appropriate method for converting Seurat v4 data into Anndata format?

[lazappi]

Hi @rainbowkiva. Currently we only support v5 Seurat objects and I think this is unlikely to change. We should make this more explicit in the dependencies and provide better warnings/errors though.

My suggested solution would be to install {Seurat} v5 and use the UpdateSeuratObject() function to update the object before passing it to write_h5ad().

[rainbowkiva]

Thanks so much for your reply @lazappi . I tried to upgrade to Seurat v5 and upgraded the v4 data to the v5 structure. After exporting it to h5ad format using write_h5ad(), when I read this file in Python, an error occurred:

library(anndataR)
anndataR::write_h5ad(
  object = d2m1_all_v5,
  path = "anndataR_v5.h5ad")

adata1 = ad.read_h5ad("anndataR_v5.h5ad")

UnicodeDecodeError: 'ascii' codec can't decode byte 0xc3 in position 4: ordinal not in range(128).

I thought it was a problem with my data, but when I used another tool to convert my data, there was no issue when reading it in Python:

library(convert2anndata)
library(anndata)
sce <- convert2anndata::convert_seurat_to_sce(d2m1_all_v5)
ad <- convert2anndata::convert_to_anndata(
  sce,
  assayName = "RNA_counts", 
  useAltExp = T )
anndata::write_h5ad(ad, "convert2anndata_v5_counts.h5ad")

adata2 = ad.read_h5ad("convert2anndata_v5.h5ad")
adata2

AnnData object with n_obs × n_vars = 633056 × 24591
obs: 'orig.ident', 'nCount_RNA', 'nFeature_RNA', 'percent.mt', 'Patient_ID', 'Cell_cluster_major', 'Cell_cluster_minor', 'Tumor_Capsule_Integrity', 'Age', 'Gender', 'AFP_μg_L', 'Tumor_Stage', 'Size_cm', 'Vascular_Invasion', 'Etiology', 'Cirrhosis', 'GS_G', 'GS_S', 'ALB_mutation', 'APOB_mutation', 'ARID1A_mutation', 'ATRX_mutation', 'AXIN1_mutation', 'CPS1_mutation', 'CTNNB1_mutation', 'KEAP1_mutation', 'KMT2C_mutation', 'RB1_mutation', 'SMARCA2_mutation', 'TP53_mutation', 'TSC2_mutation', 'Patient', 'Sample', 'Tissue_Source', 'Diagnosis', 'Tumor_Type', 'Platform', 'Sample_ID', 'log10GenesPerUMI', 'percent.rb', 'percent.hb', 'scDblFinder.class', 'scDblFinder.score', 'Contamination', 'TNM', 'Site_Major', 'Site_Minor', 'Distant_Metastasis', 'CEA', 'CA199', 'Child_Pugh', 'BCLC_Stage', 'Number_of_Lesions', 'RNA_snn_res.0.01', 'RNA_snn_res.0.05', 'RNA_snn_res.0.08', 'RNA_snn_res.0.1', 'RNA_snn_res.0.2', 'RNA_snn_res.0.5', 'RNA_snn_res.0.8', 'RNA_snn_res.1', 'Cell_cluster_res.1', 'Cell_cluster_res.0.05'
var: 'vst.mean', 'vst.variance', 'vst.variance.expected', 'vst.variance.standardized', 'vst.variable'
obsm: 'X_harmony', 'X_pca', 'X_tsne', 'X_tsne_naive', 'X_umap', 'X_umap_naive'

[lazappi]

Thanks so much for your reply @lazappi . I tried to upgrade to Seurat v5 and upgraded the v4 data to the v5 structure. After exporting it to h5ad format using write_h5ad(), when I read this file in Python, an error occurred:

@rainbowkiva I think this is a separate problem so I have created a new issue #400. I will reply there.