<p>If adapter sequences don't appear in the reference database, or won't be mapped to any sequences in the reference database, then removal is unnecessary for any quantification.</p>
<p>Adapter removal is also rarely needed prior to downstream processing with analysis suites, because they usually have any necessary filtering/removal built into the workflows.</p>

CC BY-SA 4.0
2024-11-15T05:12:43.117Z
2024-11-15T09:15:55.683Z
2024-11-15T09:15:55.683Z
gringer
<p>You are overthinking this.  Just use cellranger.  The stuff in R1 after the cell barcode and UMI is garbage. Cellranger knows that.</p>

CC BY-SA 4.0
2024-11-15T01:51:40.940Z
Thank you for your answer, so do I still need to do quality control like other NGS processes, such as adapter trim?
zhang
CC BY-SA 4.0
2024-11-18T16:44:45.417Z
You don't really have to do adapter trim at all with RNASeq.  First of all, why would your reads be so short that you would read through to the adapter?  Second, STAR is a gapped aligner, it has no problem soft-clipping reads to get them to align.  Third, even if it didn't, what are the odds that it would matter?  You are just gene counting, so as long as a read gets counted as belonging to the right gene, it doesn't matter if there's cruft at the end.
swbarnes2
CC BY-SA 4.0
2024-11-19T03:35:07.760Z
Thank you for your answer, I belive you have answered my question very well. In fact, I just got involved in the analysis of scRNA-seq (I was previously engaged in genome analysis). We have completed the scRNA-seq from the sequencing company. The guide they provided suggesting checking and removing the adapter before downstream analysis, which made me confused because in my impression the insert size of the 10x platform is long than typic NGS. But I guess you have answered my question very well, thank you again.
zhang
CC BY-SA 4.0
2024-11-14T16:36:21.407Z
2024-11-14T16:36:21.407Z
swbarnes2
<p>I am trying to process some upstream data of single-cell sequencing, which are based on the 10x platform. They come directly from the output of <code>bcl2fastq</code>, so they are very raw and contain adapter sequences.</p>
<p>I first referred to the guide of cellranger (<a href="https://www.10xgenomics.com/support/software/cell-ranger/latest/analysis/running-pipelines/cr-gex-count" rel="nofollow noreferrer">https://www.10xgenomics.com/support/software/cell-ranger/latest/analysis/running-pipelines/cr-gex-count</a>). In the guide of cellranger, the steps to process these raw data seem to be simple. Basic steps are:</p>
<pre><code>makefasta(bcl2fastq) --&gt; cellranger count --&gt; counts matrix --&gt; other analysis

</code></pre>
<p>The questions I am concerned about are:</p>
<ol>
<li><p>Is it necessary to apply standard NGS processing procedures, such as adapter removal and trimming of low-quality reads, which are not mentioned in the cellranger document?</p>
</li>
<li><p>I noticed that the R1 of fastq generated by the usual 10x genomic platform is mostly 26bp reads, which contains the information of umi index. But our data seem more complex, its looks have a ploy(T) tail and other sequence:</p>
</li>
</ol>
<pre><code>@A00199:1157:HKXC:2:1101:9914:1501 1:N:0:CACAATCCC+TTGTGGATA
ATCGTCCTCGGAGTGACGGTAATTCAGCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGGACTGGATTTTTATTTTTATTAAACTGGGGGTTTATTAAAAAAAGAAACAAGATGAACC
+
FFFFFFFFFFFFFFF:FFFF,:FFFFF::,FFF:F,F:FFF:F:FF,F:FFFFFFF,FF,,F,,,,,,,:FF,,,FFF,,,,,:,,,,,:,,,,,:F,:F,,,::,,,,,,,,,,,,,,,
</code></pre>
<p>Do I need to further process the R1 data?</p>
<ol start="3">
<li>Are there any classic related processes for reference?</li>
</ol>
<p>Thanks for any suggestions.</p>

CC BY-SA 4.0
2024-11-15T10:25:29.740Z
Ask them https://community.illumina.com/s/
pippo1980
<scrnaseq><ngs><fastq>
Upstream processing of raw single-cell sequencing data from bcl2fastq
# Upstream processing of raw single-cell sequencing data from bcl2fastq

(Asked by: username_0 on 2024-11-14)

I am trying to process some upstream data of single-cell sequencing, which are based on the 10x platform. They come directly from the output of bcl2fastq, so they are very raw and contain adapter sequences.
I first referred to the guide of cellranger (https://www.10xgenomics.com/support/software/cell-ranger/latest/analysis/running-pipelines/cr-gex-count). In the guide of cellranger, the steps to process these raw data seem to be simple. Basic steps are:
makefasta(bcl2fastq) --> cellranger count --> counts matrix --> other analysis


The questions I am concerned about are:

Is it necessary to apply standard NGS processing procedures, such as adapter removal and trimming of low-quality reads, which are not mentioned in the cellranger document?

I noticed that the R1 of fastq generated by the usual 10x genomic platform is mostly 26bp reads, which contains the information of umi index. But our data seem more complex, its looks have a ploy(T) tail and other sequence:


@A00199:1157:HKXC:2:1101:9914:1501 1:N:0:CACAATCCC+TTGTGGATA
ATCGTCCTCGGAGTGACGGTAATTCAGCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGGACTGGATTTTTATTTTTATTAAACTGGGGGTTTATTAAAAAAAGAAACAAGATGAACC
+
FFFFFFFFFFFFFFF:FFFF,:FFFFF::,FFF:F,F:FFF:F:FF,F:FFFFFFF,FF,,F,,,,,,,:FF,,,FFF,,,,,:,,,,,:,,,,,:F,:F,,,::,,,,,,,,,,,,,,,

Do I need to further process the R1 data?

Are there any classic related processes for reference?

Thanks for any suggestions.

**Tags:** scrnaseq, ngs, fastq
> **Comments:**
> **username_1**: Ask them https://community.illumina.com/s/  

---

## 2 answers

### Answer by username_3 on 2024-11-14. Score: 4 | Accepted answer

You are overthinking this. Just use cellranger. The stuff in R1 after the cell barcode and UMI is garbage. Cellranger knows that.

> **Comments:**
> **username_0**: Thank you for your answer, so do I still need to do quality control like other NGS processes, such as adapter trim?  
> **username_3**: You don't really have to do adapter trim at all with RNASeq.  First of all, why would your reads be so short that you would read through to the adapter?  Second, STAR is a gapped aligner, it has no problem soft-clipping reads to get them to align.  Third, even if it didn't, what are the odds that it would matter?  You are just gene counting, so as long as a read gets counted as belonging to the right gene, it doesn't matter if there's cruft at the end.  
> **username_0**: Thank you for your answer, I belive you have answered my question very well. In fact, I just got involved in the analysis of scRNA-seq (I was previously engaged in genome analysis). We have completed the scRNA-seq from the sequencing company. The guide they provided suggesting checking and removing the adapter before downstream analysis, which made me confused because in my impression the insert size of the 10x platform is long than typic NGS. But I guess you have answered my question very well, thank you again.  

---

### Answer by username_2 on 2024-11-15. Score: 1

If adapter sequences don't appear in the reference database, or won't be mapped to any sequences in the reference database, then removal is unnecessary for any quantification.

Adapter removal is also rarely needed prior to downstream processing with analysis suites, because they usually have any necessary filtering/removal built into the workflows.


---

