<p>From what was described, mostly likely they ran cellranger and usually you can get <a href="https://cf.10xgenomics.com/samples/cell-exp/4.0.0/Parent_NGSC3_DI_PBMC/Parent_NGSC3_DI_PBMC_web_summary.html" rel="nofollow noreferrer">a summary report like this</a></p>
<p>One of the metric would be <code>Fraction Reads in Cells</code> and I think this is what they are referring to this.</p>
<p>My suggestion would be to ask for the report from cellranger and check the metrics and the different plots. If what you have are indeed pbmcs, the reason is most likely not a lot of cells made it into droplets.</p>
<p>Submitting another sample will not help unless you can ensure the cells are of good enough quality, otherwise you will not get much cells back</p>
<p>Sequencing it deeper does not help as well because you are basically sequencing RNA of so called ambient DNA, and it does not give you useful information.</p>

CC BY-SA 4.0
2021-06-16T16:13:55.477Z
2021-06-16T16:13:55.477Z
StupidWolf
<p><em>Answer from @devon-ryan, converted from comment:</em></p>
<p>Comparing with matched bulk RNA-seq isn't reasonably related to this, unless you want to ensure the pseudo-bulk is similarish to the actual bulk. Of course they'll be different, but I suppose if you had enough samples and enough background knowledge about what to expect maybe you could get an idea whether the pseudo-bulk way reasonable, which would hit at whether the scRNA-seq was OK. But realistically you'd need a lot of experience with these exact cells in bulk and scRNA-seq to do that. Otherwise, it's a waste of time.</p>

CC BY-SA 4.0
2021-06-15T10:21:46.657Z
2021-06-15T10:21:46.657Z
gringer
<p>Can you please help me in a technical issue? We sent some samples to single cell sequencing The company says</p>
<blockquote>
<p>Many of the reads were not assigned to cell-associated barcodes. This
could be caused by high levels of ambient RNA or by a significant
population of cells with a low RNA content, which the algorithm did
not call as cells. The latter case can be addressed by inspecting the
data to determine the appropriate cell count and using --force-cells.</p>
<p>This would happen if the cells aren’t transcriptionally active – but
as these are PBMCs this is unusual .</p>
</blockquote>
<p>Have you ever heard about such a problem? Any solution in this case? sending more sample of each patient for sequencing or comparing single cell with matched bulk RNA-seq which one help?</p>
<p>10X say they would do deep sequencing (covering the cost) to get something for us but I don't know why my boss says we should compare single cell with matched bulk RNA-seq.</p>

CC BY-SA 4.0
2021-06-14T15:26:54.367Z
This is not a bioinformatics problem, it's a sample/library prep problem.
swbarnes2
CC BY-SA 4.0
2021-06-14T18:33:39.323Z
Are these single cells or single nuclei? Fresh or preserved in some way?
Chris_Rands
CC BY-SA 4.0
2021-06-14T18:34:22.270Z
Agreed, but further bioinformatics might help better diagnose the issue, e.g. fastQC
Chris_Rands
CC BY-SA 4.0
2023-05-04T18:44:00.967Z
@Chris_Rands Do we expect a different Fraction of reads in cell?
CuriousS
<10x-genomics>
10X single cell sequencing issue
# 10X single cell sequencing issue

(Asked by: username_0 on 2021-06-14)

Can you please help me in a technical issue? We sent some samples to single cell sequencing The company says

> Many of the reads were not assigned to cell-associated barcodes. This
> could be caused by high levels of ambient RNA or by a significant
> population of cells with a low RNA content, which the algorithm did
> not call as cells. The latter case can be addressed by inspecting the
> data to determine the appropriate cell count and using --force-cells.
>
> This would happen if the cells aren’t transcriptionally active – but
> as these are PBMCs this is unusual .

Have you ever heard about such a problem? Any solution in this case? sending more sample of each patient for sequencing or comparing single cell with matched bulk RNA-seq which one help?

10X say they would do deep sequencing (covering the cost) to get something for us but I don't know why my boss says we should compare single cell with matched bulk RNA-seq.

**Tags:** 10x-genomics
> **Comments:**
> **username_1**: This is not a bioinformatics problem, it's a sample/library prep problem.  
> **username_2**: Are these single cells or single nuclei? Fresh or preserved in some way?  
> **username_2**: Agreed, but further bioinformatics might help better diagnose the issue, e.g. fastQC  
> **username_3**: @Chris_Rands Do we expect a different Fraction of reads in cell?  

---

## 2 answers

### Answer by username_4 on 2021-06-16. Score: 1

From what was described, mostly likely they ran cellranger and usually you can get [a summary report like this](https://cf.10xgenomics.com/samples/cell-exp/4.0.0/Parent_NGSC3_DI_PBMC/Parent_NGSC3_DI_PBMC_web_summary.html)

One of the metric would be `Fraction Reads in Cells` and I think this is what they are referring to this.

My suggestion would be to ask for the report from cellranger and check the metrics and the different plots. If what you have are indeed pbmcs, the reason is most likely not a lot of cells made it into droplets.

Submitting another sample will not help unless you can ensure the cells are of good enough quality, otherwise you will not get much cells back

Sequencing it deeper does not help as well because you are basically sequencing RNA of so called ambient DNA, and it does not give you useful information.


---

### Answer by username_5 on 2021-06-15. Score: 0

*Answer from @devon-ryan, converted from comment:*

Comparing with matched bulk RNA-seq isn't reasonably related to this, unless you want to ensure the pseudo-bulk is similarish to the actual bulk. Of course they'll be different, but I suppose if you had enough samples and enough background knowledge about what to expect maybe you could get an idea whether the pseudo-bulk way reasonable, which would hit at whether the scRNA-seq was OK. But realistically you'd need a lot of experience with these exact cells in bulk and scRNA-seq to do that. Otherwise, it's a waste of time.


---

