<p>Yes, &quot;low fraction reads in cells&quot; is more common with snRNA-seq from frozen samples, I wouldn't worry about it by itself (you're just throwing away some sequencing data). You should still check though that the other QC metrics are good. In particular, sometimes such samples have an unclear seperation of cells from empty droplets on the UMI rank plot and the consequent estimated cell count is off, requiring alternative approaches to distinguish cellular droplets from ambient RNA etc.</p>

CC BY-SA 4.0
2023-05-07T18:30:17.163Z
Thanks a lot Chris. I am thinking about more sophisticated pipeline like CellBender etc. I just wanted opinions for professional more experienced than me because I have not dealt with non-standard snRNA-seq data a lot.
CuriousS
CC BY-SA 4.0
2023-05-07T18:15:42.207Z
2023-05-07T18:15:42.207Z
Chris_Rands
<p>For some of our snRNA-seq samples we are finding low fraction of reads detected in single-nuclei rna-seq samples from cellranger, while the other metrics are perfect.</p>
<p>While I understand this could be caused by library preparation and abundance of ambient RNA. Just wondering if this behavior is expected for single-nuclei datasets. My confusion is specifically coming from the fact that 10X website also has such a sample that has low number of fraction reads in cells.</p>
<p><a href="https://cf.10xgenomics.com/samples/cell-exp/7.0.0/5k_mouse_brain_CNIK_3pv3/5k_mouse_brain_CNIK_3pv3_web_summary.html" rel="nofollow noreferrer">https://cf.10xgenomics.com/samples/cell-exp/7.0.0/5k_mouse_brain_CNIK_3pv3/5k_mouse_brain_CNIK_3pv3_web_summary.html</a></p>
<p>Would love to know if this behavior is expected or seen often who are more experienced in snRNA-seq. The metric documentation page is <a href="https://kb.10xgenomics.com/hc/en-us/articles/360003919491-How-to-interpret-the-Fraction-Reads-in-Cells-metric-" rel="nofollow noreferrer">here</a></p>
<p>Here is snapshot from 10X report
<a href="https://i.sstatic.net/VPMGY.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/VPMGY.png" alt="enter image description here" /></a></p>

CC BY-SA 4.0
2023-05-06T06:47:17.123Z
What do you mean by low fraction? Fraction of what (i.e. what's the denominator)? What were you expecting? What did you see instead?
gringer
CC BY-SA 4.0
2023-05-06T16:51:39.800Z
Great questions, sorry for being vague, uploaded the screen-shot for cell-ranger. low fraction - 39%, expected according to 10x 70% (if you follow the link). I am not sure how they are computing the metric though, I added the man page from 10X
CuriousS
<scrnaseq><transcriptome><cellranger>
Low fraction reads in cell metric in snRNA-seq data
# Low fraction reads in cell metric in snRNA-seq data

(Asked by: username_0 on 2023-05-04)

For some of our snRNA-seq samples we are finding low fraction of reads detected in single-nuclei rna-seq samples from cellranger, while the other metrics are perfect.

While I understand this could be caused by library preparation and abundance of ambient RNA. Just wondering if this behavior is expected for single-nuclei datasets. My confusion is specifically coming from the fact that 10X website also has such a sample that has low number of fraction reads in cells.

<https://cf.10xgenomics.com/samples/cell-exp/7.0.0/5k_mouse_brain_CNIK_3pv3/5k_mouse_brain_CNIK_3pv3_web_summary.html>

Would love to know if this behavior is expected or seen often who are more experienced in snRNA-seq. The metric documentation page is [here](https://kb.10xgenomics.com/hc/en-us/articles/360003919491-How-to-interpret-the-Fraction-Reads-in-Cells-metric-)

Here is snapshot from 10X report
[![enter image description here](https://i.sstatic.net/VPMGY.png)](https://i.sstatic.net/VPMGY.png)

**Tags:** scrnaseq, transcriptome, cellranger
> **Comments:**
> **username_1**: What do you mean by low fraction? Fraction of what (i.e. what's the denominator)? What were you expecting? What did you see instead?  
> **username_0**: Great questions, sorry for being vague, uploaded the screen-shot for cell-ranger. low fraction - 39%, expected according to 10x 70% (if you follow the link). I am not sure how they are computing the metric though, I added the man page from 10X  

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## 1 answers

### Answer by username_2 on 2023-05-07. Score: 1

Yes, "low fraction reads in cells" is more common with snRNA-seq from frozen samples, I wouldn't worry about it by itself (you're just throwing away some sequencing data). You should still check though that the other QC metrics are good. In particular, sometimes such samples have an unclear seperation of cells from empty droplets on the UMI rank plot and the consequent estimated cell count is off, requiring alternative approaches to distinguish cellular droplets from ambient RNA etc.

> **Comments:**
> **username_0**: Thanks a lot Chris. I am thinking about more sophisticated pipeline like CellBender etc. I just wanted opinions for professional more experienced than me because I have not dealt with non-standard snRNA-seq data a lot.  

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