<p>For what it's worth, we always use CellRanger <code>count</code> to quantify both gene expression and hashtags / surface features. Note that <code>count</code> does not demultiplexing. It just tells how which barcode (that is cell) has how many counts for which surface feature. The actual demultiplexing, so deciding which cell has sufficient counts for a given feature to &quot;trust&quot; it or to decide which cell(s) qualify as &quot;positive&quot; for a feature is typically done downstream. I like <code>hashedDrops</code> from <a href="https://www.bioconductor.org/packages/release/bioc/html/DropletUtils.html" rel="nofollow noreferrer">DropletUtils</a> for it, but many other packages exist as well.</p>

CC BY-SA 4.0
2024-07-02T13:48:11.373Z
Thank you for the reply. Does it sound correct to you then to use hashsolo after cellranger count? It does seem like the hashtag information is on the .var instead of .obs but I found a few links with information on how to adjust the commands to get it to work.
pythonbeginner
CC BY-SA 4.0
2024-07-03T11:39:15.780Z
I don't know what obs and var is, but generally yes, you can use any downstream demultiplexer here. The counts for the hashes are on the tail of the count matrix generated by cellranger.
ATpoint
CC BY-SA 4.0
2024-07-02T06:28:57.137Z
2024-07-02T06:28:57.137Z
ATpoint
<p>There are two different kinds of sample index sequences.  One is found in the part of the read that is the index reads on the instrument, the other is embedded in the read itself.</p>
<p>Indices found in the index read are handled by whatever you use to make fastqs from bcls, so either bcl2fastq, or bcl-convert, or cellranger mkfastq on versions before 9.0 (which just has a wrapper around bcl2fastq).</p>
<p>If you have fastqs that are named &quot;sample1&quot;, &quot;sample2&quot;, then these sample indices were used, and the samples have been split.</p>
<p>The other kind of sample indices are in the read itself.  Cellranger multi will handle these.  You would be told what sample has what barcode, and the barcodes have names like BC001.</p>
<p>It's probably more straightforward to put samples split by index read into STARSolo.  I'm not sure how STARSolo will handle reads win internal barcode.  But if your fastqs are already split by sample, your samples might be already properly and totally demultiplexed, so you could use starsolo if you wanted.</p>

CC BY-SA 4.0
2024-12-02T18:14:03.093Z
2024-12-02T18:14:03.093Z
swbarnes2
<p>I have a set of fastq files. One of them is for the gene expression data and the other is feature barcode data which contain hashtag information.
I was told to use cellranger count for feature barcode and then hash solo to demultiplex the hashtags. However, I saw that 10X says we can use cellranger multi to demultiplex hashtags. Are these 2 methods very different? Which one is more appropriate?</p>
<p>Thank you</p>

<single-cell><cellranger>
Should I use cellranger count or multi for biolegend hashtags?
# Should I use cellranger count or multi for biolegend hashtags?

(Asked by: username_0 on 2024-07-01)

I have a set of fastq files. One of them is for the gene expression data and the other is feature barcode data which contain hashtag information.
I was told to use cellranger count for feature barcode and then hash solo to demultiplex the hashtags. However, I saw that 10X says we can use cellranger multi to demultiplex hashtags. Are these 2 methods very different? Which one is more appropriate?

Thank you

**Tags:** single-cell, cellranger

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## 2 answers

### Answer by username_1 on 2024-07-02. Score: 0

For what it's worth, we always use CellRanger `count` to quantify both gene expression and hashtags / surface features. Note that `count` does not demultiplexing. It just tells how which barcode (that is cell) has how many counts for which surface feature. The actual demultiplexing, so deciding which cell has sufficient counts for a given feature to "trust" it or to decide which cell(s) qualify as "positive" for a feature is typically done downstream. I like `hashedDrops` from [DropletUtils](https://www.bioconductor.org/packages/release/bioc/html/DropletUtils.html) for it, but many other packages exist as well.

> **Comments:**
> **username_0**: Thank you for the reply. Does it sound correct to you then to use hashsolo after cellranger count? It does seem like the hashtag information is on the .var instead of .obs but I found a few links with information on how to adjust the commands to get it to work.  
> **username_1**: I don't know what obs and var is, but generally yes, you can use any downstream demultiplexer here. The counts for the hashes are on the tail of the count matrix generated by cellranger.  

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### Answer by username_2 on 2024-12-02. Score: 0

There are two different kinds of sample index sequences. One is found in the part of the read that is the index reads on the instrument, the other is embedded in the read itself.

Indices found in the index read are handled by whatever you use to make fastqs from bcls, so either bcl2fastq, or bcl-convert, or cellranger mkfastq on versions before 9.0 (which just has a wrapper around bcl2fastq).

If you have fastqs that are named "sample1", "sample2", then these sample indices were used, and the samples have been split.

The other kind of sample indices are in the read itself. Cellranger multi will handle these. You would be told what sample has what barcode, and the barcodes have names like BC001.

It's probably more straightforward to put samples split by index read into STARSolo. I'm not sure how STARSolo will handle reads win internal barcode. But if your fastqs are already split by sample, your samples might be already properly and totally demultiplexed, so you could use starsolo if you wanted.


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