Data retention and privacy
- Uploaded files are used only to run the requested job.
- Uploaded files are not used to retrain or improve the scMaize model.
- Anyone with the private status link can access that job result during the retention window.
SCmaize
Asynchronous maize single-cell model services
scMaize
Maize single-cell atlas
| Job | App | Status | Created | Result |
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Use this guide to prepare input files, download examples, understand job retention, and interpret output files.
.X: cells x genes expression matrix
.obs: one row per cell
.var_names: maize gene symbols or stable IDs, for example Zm00001d021668
Input a query `.h5ad` file. Optionally provide a custom reference `.h5ad` with `obs` columns named `tissue` and `cell_type`; otherwise the production scMaize atlas reference is used.
Use `Tissue restriction` when the query is known to come from one tissue, for example `Root`. In advanced options, `Neighbors` controls how many nearest reference cells vote during label transfer. The default is 30.
Output is a CSV with `predicted_cell_type`, `predicted_tissue`, and `confidence`. Confidence summarizes agreement among nearest reference neighbors, not an absolute probability.
Query: test_query_multi.h5ad
Reference: test_reference_multi.h5ad
Neighbors: 30
Result: scmaize_annotations.csv
test_query_multi.h5adDownload query
test_reference_multi.h5adDownload reference
eval_reference.h5adDownload larger reference
eval_root_qry.h5adDownload root query
eval_root_ref.h5adDownload root reference
Input a query `.h5ad` file. `standard` mode returns CLS cell embeddings. `dualStream` combines CLS embeddings with PCA expression components for a richer cell-state representation.
Output is a NumPy `.npy` matrix with one row per cell. In `standard` mode with default settings, `test_query_multi.h5ad` produces a `100 x 384` matrix. In `dualStream` with `Embedding dim = 128` and `PCA dim = 64`, it produces a `100 x 192` matrix.
Query: test_query_multi.h5ad
Mode: dualStream
Embedding dim: 128
PCA dim: 64
Result: scmaize_embeddings.npy
test_query_multi.h5adDownload query
Input a query `.h5ad` file. The tool uses gene-neighbor relationships from scMaize gene embeddings to estimate sparse or missing expression values.
`Neighbors` controls how many similar genes contribute to each imputed value. The default is 10. Output is an imputed `.h5ad` matrix with the same cell and gene axes as the input.
Query: test_query_multi.h5ad
Model: scMaizeGO
Neighbors: 10
Result: scmaize_imputed.h5ad
test_query_multi.h5adDownload query
No `.h5ad` file is required. Enter comma-separated maize gene symbols or stable IDs.
Output is a ranked CSV table with the query gene, matched similar gene, rank, and similarity score. Similarity is computed in scMaize gene embedding space and should be interpreted as functional relatedness.
Genes: CYP704B1, Zm00001d021668
Top N: 10
Model: scMaizeGO
Result: scmaize_similarity.csv
The example `.h5ad` files are lightweight maize single-cell RNA-seq datasets for smoke testing and format reference. They include multi-tissue query/reference files and Root-only query/reference files. The small bundled reference file is an example template for custom reference format, not the production annotation reference used by default.