> ## 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.

# RunPresto() / RunPrestoAll()

> Fast Wilcoxon rank-sum test for differential expression using Presto

SeuratWrappers provides two Presto-based differential expression functions:

* **`RunPresto()`** — Drop-in replacement for `FindMarkers()` using Presto's fast Wilcoxon test
* **`RunPrestoAll()`** — Drop-in replacement for `FindAllMarkers()` using Presto

Both functions temporarily swap Seurat's internal `WilcoxDETest` with Presto's implementation, which is \~1000x faster for large datasets.

## RunPresto()

### Syntax

```r theme={null}
RunPresto(
  object,
  ident.1 = NULL,
  ident.2 = NULL,
  group.by = NULL,
  subset.ident = NULL,
  assay = NULL,
  slot = "data",
  reduction = NULL,
  features = NULL,
  logfc.threshold = 0.25,
  test.use = "wilcox",
  min.pct = 0.1,
  min.diff.pct = -Inf,
  verbose = TRUE,
  only.pos = FALSE,
  max.cells.per.ident = Inf,
  random.seed = 1,
  latent.vars = NULL,
  min.cells.feature = 3,
  min.cells.group = 3,
  mean.fxn = NULL,
  fc.name = NULL,
  base = 2,
  ...
)
```

### Parameters

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

<ParamField path="ident.1" type="character" default="NULL">
  Identity class to define as positive. If `NULL`, uses all identities.
</ParamField>

<ParamField path="ident.2" type="character" default="NULL">
  Identity class to compare against. If `NULL`, uses all other cells.
</ParamField>

<ParamField path="group.by" type="character" default="NULL">
  Metadata column to use for grouping cells instead of active identities.
</ParamField>

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

<ParamField path="slot" type="character" default="data">
  Slot within the assay to use.
</ParamField>

<ParamField path="logfc.threshold" type="numeric" default="0.25">
  Minimum log fold-change threshold for reporting genes.
</ParamField>

<ParamField path="min.pct" type="numeric" default="0.1">
  Minimum fraction of cells expressing the gene in either group.
</ParamField>

<ParamField path="only.pos" type="logical" default="FALSE">
  Return only positive markers.
</ParamField>

<ParamField path="max.cells.per.ident" type="numeric" default="Inf">
  Maximum number of cells per identity class (downsamples for speed).
</ParamField>

## RunPrestoAll()

### Syntax

```r theme={null}
RunPrestoAll(
  object,
  assay = NULL,
  features = NULL,
  logfc.threshold = 0.25,
  test.use = "wilcox",
  slot = "data",
  min.pct = 0.1,
  min.diff.pct = -Inf,
  node = NULL,
  verbose = TRUE,
  only.pos = FALSE,
  max.cells.per.ident = Inf,
  random.seed = 1,
  latent.vars = NULL,
  min.cells.feature = 3,
  min.cells.group = 3,
  mean.fxn = NULL,
  fc.name = NULL,
  base = 2,
  return.thresh = 0.01,
  ...
)
```

### Additional Parameters

<ParamField path="return.thresh" type="numeric" default="0.01">
  Only return markers with adjusted p-value below this threshold.
</ParamField>

## Returns

A data frame identical to the output of `FindMarkers()` / `FindAllMarkers()`, containing columns: `p_val`, `avg_log2FC`, `pct.1`, `pct.2`, `p_val_adj`.

## Examples

```r theme={null}
library(SeuratWrappers)
remotes::install_github("immunogenomics/presto")

# Find markers for one cluster
markers_14 <- RunPresto(object, ident.1 = "14", ident.2 = NULL)

# Find all markers
all_markers <- RunPrestoAll(object, only.pos = TRUE, logfc.threshold = 0.5)
top5 <- all_markers %>% group_by(cluster) %>% top_n(5, avg_log2FC)
```

## See Also

* [Presto method guide](/methods/presto)