> ## 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.

# RunFastMNN() / FastMNNIntegration()

> Mutual nearest neighbor batch correction using the batchelor package

SeuratWrappers provides two fastMNN integration functions:

* **`RunFastMNN()`** — For Seurat v4-style workflows using a list of Seurat objects
* **`FastMNNIntegration()`** — For Seurat v5-style workflows using `IntegrateLayers()`

## RunFastMNN()

### Syntax

```r theme={null}
RunFastMNN(
  object.list,
  assay = NULL,
  features = 2000,
  reduction.name = "mnn",
  reduction.key = "mnn_",
  reconstructed.assay = "mnn.reconstructed",
  verbose = TRUE,
  ...
)
```

### Parameters

<ParamField path="object.list" type="list" required>
  A list of two or more Seurat objects to integrate.
</ParamField>

<ParamField path="assay" type="character" default="NULL">
  Assay to use for integration. Defaults to the active default assay of the first object.
</ParamField>

<ParamField path="features" type="integer or character vector" default="2000">
  If an integer, selects that many integration features via `SelectIntegrationFeatures()`. If a character vector, uses those specific features.
</ParamField>

<ParamField path="reduction.name" type="character" default="mnn">
  Name for the MNN-corrected embedding stored as a DimReduc object.
</ParamField>

<ParamField path="reduction.key" type="character" default="mnn_">
  Column name prefix for the MNN embedding dimensions.
</ParamField>

<ParamField path="reconstructed.assay" type="character" default="mnn.reconstructed">
  Name of the assay storing the batch-corrected gene expression matrix.
</ParamField>

<ParamField path="verbose" type="logical" default="TRUE">
  Print progress messages.
</ParamField>

<ParamField path="..." type="any">
  Additional parameters passed to `batchelor::fastMNN()` (e.g., `k` for number of nearest neighbors).
</ParamField>

### Returns

A merged Seurat object with:

* A DimReduc under `reduction.name` containing MNN-corrected embeddings
* A new assay under `reconstructed.assay` with batch-corrected expression values
* Integration metadata stored in the `Tool` slot

## FastMNNIntegration()

For use with Seurat v5's `IntegrateLayers()` function.

### Syntax

```r theme={null}
FastMNNIntegration(
  object,
  assay = NULL,
  orig = NULL,
  groups = NULL,
  layers = NULL,
  scale.layer = NULL,
  features = 2000,
  new.reduction = "integrated.mnn",
  reduction.key = "mnn_",
  reconstructed.assay = "mnn.reconstructed",
  verbose = TRUE,
  ...
)
```

### Parameters

<ParamField path="object" type="Seurat" required>
  A Seurat v5 object with split layers (one per batch).
</ParamField>

<ParamField path="features" type="integer or character vector" default="2000">
  Number of integration features or a character vector of specific features.
</ParamField>

<ParamField path="new.reduction" type="character" default="integrated.mnn">
  Name for the integrated reduction.
</ParamField>

<ParamField path="reduction.key" type="character" default="mnn_">
  Prefix for embedding dimension names.
</ParamField>

## Examples

```r theme={null}
library(SeuratWrappers)
BiocManager::install("batchelor")

# Seurat v4 style
object <- RunFastMNN(object.list = SplitObject(merged, split.by = "batch"))

# Seurat v5 style
object <- IntegrateLayers(
  object = merged,
  method = FastMNNIntegration,
  new.reduction = "integrated.mnn",
  verbose = FALSE
)
```

## See Also

* [fastMNN method guide](/methods/fast-mnn)