> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/satijalab/seurat-wrappers/llms.txt
> Use this file to discover all available pages before exploring further.

# as.cell_data_set() / as.Seurat.cell_data_set()

> Convert between Seurat objects and Monocle 3 cell_data_set objects

SeuratWrappers provides two-way conversion between Seurat objects and Monocle 3 `cell_data_set` objects.

## as.cell\_data\_set()

Converts a Seurat object to a Monocle 3 `cell_data_set` for trajectory analysis.

### Syntax

```r theme={null}
as.cell_data_set(
  x,
  assay = DefaultAssay(object = x),
  reductions = AssociatedDimReducs(object = x, assay = assay),
  default.reduction = DefaultDimReduc(object = x, assay = assay),
  graph = paste0(assay, "_snn"),
  group.by = NULL,
  ...
)
```

### Parameters

<ParamField path="x" type="Seurat" required>
  A Seurat object to convert.
</ParamField>

<ParamField path="assay" type="character">
  Assay to use. Defaults to the active default assay.
</ParamField>

<ParamField path="reductions" type="character vector">
  Names of dimensional reductions to transfer. Defaults to all reductions associated with `assay` plus global reductions.
</ParamField>

<ParamField path="default.reduction" type="character">
  Name of the reduction to use as the primary clustering reduction in Monocle 3. Defaults to the default DimReduc (UMAP > tSNE > PCA).
</ParamField>

<ParamField path="graph" type="character">
  Name of the nearest-neighbor graph to transfer for clustering. Defaults to `<assay>_snn`.
</ParamField>

<ParamField path="group.by" type="character" default="NULL">
  Metadata column to use for cell identities. If `NULL`, uses the active Seurat identities.
</ParamField>

### What gets transferred

| Seurat                                               | Monocle 3                      | Notes                                    |
| ---------------------------------------------------- | ------------------------------ | ---------------------------------------- |
| `Embeddings`                                         | `reducedDims`                  | Names uppercased (e.g., `umap` → `UMAP`) |
| Feature loadings                                     | `reduce_dim_aux$gene_loadings` | Last reduction only                      |
| `Stdev`                                              | `reduce_dim_aux$prop_var_expl` | Last reduction only                      |
| Seurat clusters                                      | `clusters` slot                | With nearest-neighbor graph              |
| `monocle3_clusters` / `monocle3_partitions` metadata | `clusters` slot                | If present, used directly                |

<Warning>
  Monocle 3 trajectory inference requires cell partitions, which Seurat does not compute. After conversion, run `cluster_cells()` on the `cell_data_set` to generate partitions before calling `learn_graph()`.
</Warning>

## as.Seurat.cell\_data\_set()

Converts a Monocle 3 `cell_data_set` back to a Seurat object.

### Syntax

```r theme={null}
as.Seurat(
  x,
  counts = "counts",
  data = NULL,
  assay = "RNA",
  project = "cell_data_set",
  loadings = NULL,
  clusters = NULL,
  ...
)
```

### Parameters

<ParamField path="x" type="cell_data_set" required>
  A Monocle 3 `cell_data_set` object.
</ParamField>

<ParamField path="counts" type="character" default="counts">
  Name of the assay in the `cell_data_set` to use as counts.
</ParamField>

<ParamField path="assay" type="character" default="RNA">
  Name for the assay in the resulting Seurat object.
</ParamField>

<ParamField path="loadings" type="character" default="NULL">
  Name of the reduction to transfer gene loadings into. Defaults to the first reduction containing `"pca"` (case-insensitive). Pass `NA` to suppress loadings transfer.
</ParamField>

<ParamField path="clusters" type="character" default="NULL">
  Name of the Monocle clustering method to use for Seurat identities. Defaults to `DefaultDimReduc(object)`.
</ParamField>

### What gets transferred back

| Monocle 3                      | Seurat                                         | Notes                     |
| ------------------------------ | ---------------------------------------------- | ------------------------- |
| `reduce_dim_aux$gene_loadings` | `Loadings` of `loadings` reduction             |                           |
| Monocle clusters               | Active identity + `monocle3_clusters` metadata |                           |
| Monocle partitions             | `monocle3_partitions` metadata                 |                           |
| Monocle pseudotime             | `monocle3_pseudotime` metadata                 |                           |
| Nearest-neighbor graph         | `<assay>_monocle3_graph`                       | Converted to Seurat Graph |

## Examples

```r theme={null}
library(SeuratWrappers)
remotes::install_github("cole-trapnell-lab/monocle3")

# Seurat → Monocle 3
cds <- as.cell_data_set(seurat_obj)
cds <- cluster_cells(cds)
cds <- learn_graph(cds)
cds <- order_cells(cds)

# Monocle 3 → Seurat
seurat_obj <- as.Seurat(cds)
```

## See Also

* [Monocle 3 method guide](/methods/monocle3)