> ## 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.

# RunMiQC() / PlotMiQC()

> Probabilistic quality control for single-cell datasets using mixture models

SeuratWrappers provides two functions for miQC-based quality control:

* **`RunMiQC()`** — Fits a mixture model and marks cells as compromised
* **`PlotMiQC()`** — Visualizes the fitted model and posterior probabilities

## RunMiQC()

### Syntax

```r theme={null}
RunMiQC(
  object,
  percent.mt = "percent.mt",
  nFeature_RNA = "nFeature_RNA",
  posterior.cutoff = 0.75,
  model.type = "linear",
  model.slot = "flexmix_model",
  verbose = TRUE,
  backup.option = "percentile",
  backup.percentile = 0.99,
  backup.percent = 5,
  ...
)
```

### Parameters

<ParamField path="object" type="Seurat" required>
  A Seurat object with mitochondrial percentage and feature count metadata.
</ParamField>

<ParamField path="percent.mt" type="character" default="percent.mt">
  Name of the metadata column containing percent mitochondrial reads.
</ParamField>

<ParamField path="nFeature_RNA" type="character" default="nFeature_RNA">
  Name of the metadata column containing the number of detected features.
</ParamField>

<ParamField path="posterior.cutoff" type="numeric" default="0.75">
  Cells with posterior probability of being compromised above this threshold are marked for removal.
</ParamField>

<ParamField path="model.type" type="character" default="linear">
  Type of regression model for the mixture components. One of `"linear"`, `"spline"`, or `"polynomial"`.
</ParamField>

<ParamField path="model.slot" type="character" default="flexmix_model">
  Name of the `Misc` slot in which the fitted `flexmix` model is stored.
</ParamField>

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

<ParamField path="backup.option" type="character" default="percentile">
  Fallback strategy when the mixture model cannot be fitted. One of:

  * `"percentile"` — filter by `backup.percentile`
  * `"percent"` — filter by `backup.percent` hard cutoff
  * `"pass"` — return the object without filtering
  * `"halt"` — raise an error
</ParamField>

<ParamField path="backup.percentile" type="numeric" default="0.99">
  Percentile cutoff for the `"percentile"` backup option.
</ParamField>

<ParamField path="backup.percent" type="numeric" default="5">
  Hard percent mitochondrial cutoff for the `"percent"` backup option.
</ParamField>

### Returns

A Seurat object with two new metadata columns:

* `miQC.probability` — posterior probability of each cell being compromised
* `miQC.keep` — `"keep"` or `"discard"` decision per cell

The fitted flexmix model is stored in `Misc(object, model.slot)`.

## PlotMiQC()

### Syntax

```r theme={null}
PlotMiQC(
  seurat_object,
  percent.mt = "percent.mt",
  nFeature_RNA = "nFeature_RNA",
  model.slot = "flexmix_model",
  color.by = "miQC.probability"
)
```

### Parameters

<ParamField path="seurat_object" type="Seurat" required>
  A Seurat object that has already been processed with `RunMiQC()`.
</ParamField>

<ParamField path="percent.mt" type="character" default="percent.mt">
  Metadata column name for mitochondrial percentage.
</ParamField>

<ParamField path="nFeature_RNA" type="character" default="nFeature_RNA">
  Metadata column name for number of features.
</ParamField>

<ParamField path="model.slot" type="character" default="flexmix_model">
  Name of the Misc slot containing the fitted flexmix model.
</ParamField>

<ParamField path="color.by" type="character" default="miQC.probability">
  Metadata column to use for coloring points in the plot.
</ParamField>

## Examples

```r theme={null}
library(SeuratWrappers)
install.packages("flexmix")
BiocManager::install("miQC")

# Add mitochondrial percentage
object[["percent.mt"]] <- PercentageFeatureSet(object, pattern = "^MT-")

# Run miQC
object <- RunMiQC(object, percent.mt = "percent.mt", posterior.cutoff = 0.75)

# Visualize
PlotMiQC(object)

# Filter cells
object <- subset(object, miQC.keep == "keep")
```

## See Also

* [miQC method guide](/methods/miqc)