> For the complete documentation index, see [llms.txt](https://help.connected.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.connected.illumina.com/dragen-stratamap/dragen-spatial-transcriptome/faq.md).

# FAQ

### 1. Why is my reported mtRNA % zero?

DRAGEN Spatial Transcriptome calculates mitochondrial RNA (mtRNA) by matching chromosome names in the genome's GTF file against a list of expected mitochondrial chromosome identifiers. By default, the pipeline looks for chromosomes named `chrm`, `m`, or `mt` (case-insensitive).

If your mtRNA metrics show zero or unexpectedly low values, the most likely cause is that your genome uses a different naming convention for the mitochondrial chromosome.

The pipeline reports which genes it found in the GTF and used to calculate mtRNA in the following file:

`intermediate_results/04_matrix_metrics/[samplename]/[genome]_mtRNA_genes.csv`

**How to fix this:**

You can customize which chromosome names the pipeline should recognize as mitochondrial by adding the `mitochondrial_chr` parameter to your analysis config file:

1. Create or edit your `analysis_config.json` file.
2. Add the `mitochondrial_chr` parameter with a comma-separated list of chromosome names that should be considered mitochondrial in your genome:

```
{
    "mitochondrial_chr": "NC_041761"
}
```

3. Pass this config file to the analysis using the ICA UI.

### 2. Why is my mtRNA lower than expected for a custom genome?

Even when the pipeline correctly identifies the mitochondrial chromosome, we sometimes observe a low percentage of mitochondrial counts reported for custom genomes. This is due to NUMTs (nuclear mitochondrial DNA segments), which are segments of mitochondrial DNA inserted into a nuclear chromosome. NUMTs arise when mitochondrial DNA escapes the mitochondrion, enters the nucleus, and integrates into a chromosome.

They are common across vertebrate genomes. Because NUMTs are derived from the mitochondrial genome, they share high sequence identity with it, causing RNA-seq reads from genuine mitochondrial transcripts to map equally well to both the mitochondrial chromosome and the nuclear NUMT copy. Short-read aligners will mark these as multi-mappers, and if they are discarded, the result is an artificially low mitochondrial gene count.

For example, the *Rhesus macaque* mmul10 genome has the entire mitochondrial chromosome copied into chromosome 8.

In version X of the pipeline, the ability to include multimapping reads was added. Because this prioritizes protein-coding alignments over pseudogenes, altering the annotations of the mitochondrial chromosome genes relative to the NUMTs could help solve this issue.

### 3. Why are so many of the cells in the NA cluster?

By default, DRAGEN Spatial Transcriptome filters out cells with >40% mtRNA. Depending on the sample type, this may remove a large fraction of cells. For example, in mouse heart samples, more than 40% of cells may have >40% mtRNA. To adjust the default threshold:

1. Create or edit your `analysis_config.json` file.
2. Add the `mt_threshold` parameter with a higher percentage:

```
{
    "mt_threshold": "50"
}
```

3. Pass this config file to the analysis using the ICA UI.

### 4. Why is the % of reads mapping to the genome so low?

Several factors can reduce the percentage of reads that map to the genome:

* **Custom genomes** may be incomplete, such as missing the mitochondrial chromosome, or poorly annotated. This can reduce the number of reads that align or assign to genes.
* **Poor sample quality** and/or **over-permeabilization** can produce degraded RNA. These fragments may be too short to align successfully. This is often associated with high trimming rates and a large number of reads being discarded during trimming.
* **Alignment parameters choices** such as excluding multi-mapping reads and intronic reads can decrease mapping rates. The size of effect of these settings have depends on the species, reference genome and tissue type.


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