<p>You provide Salmon with a transcriptome fasta... so merging the human transcriptome with the pox virus genome fasta file should work. You don't mention that in your post but the viral genome should exist as a fasta. You can extract the sequences from genbank or maybe you can find our virus here: <a href="https://www.ebi.ac.uk/genomes/virus.html" rel="nofollow noreferrer">https://www.ebi.ac.uk/genomes/virus.html</a></p>

<p>You can find the coding transcriptome at the link below in the <strong>cdna</strong> folder.
The non-coding transcriptome is in the <strong>ncrna</strong>. You should probably merge them:</p>

<p><a href="ftp://ftp.ensembl.org/pub/release-95/fasta/homo_sapiens/" rel="nofollow noreferrer">ftp://ftp.ensembl.org/pub/release-95/fasta/homo_sapiens/</a></p>

CC BY-SA 4.0
2019-03-24T19:18:23.870Z
Yes, I have virus genome in fasta format. I was wondering if I just concatenate in plain fasta format , the features will be missed. How do I merge so that I will have virus features included in the merged file ?  Thank you.
LoveVirology
CC BY-SA 4.0
2019-03-25T11:01:02.600Z
If you want the virus features then you would need to find the ORF/CDS regions and subset your original fasta. You could try something like: https://www.ncbi.nlm.nih.gov/orffinder/ if they are not annotated. Alternatively they might already be present in Genbank/NCBI so you could just download them from there - although I'm not familiar enough with this to tell you how to do it in a high-throughput manner.
story
CC BY-SA 4.0
2019-03-24T18:50:41.480Z
2019-03-24T18:50:41.480Z
story
<p>I did RNA-seq of mammalian cells infected with pox virus. Now, I have read files which contain both host and virus reads. I want to align the reads both to host and viral genome. I was thinking I could concatenate the host and virus genome into one file and run <a href="https://combine-lab.github.io/salmon/" rel="nofollow noreferrer">Salmon</a> against this concatenated genome.</p>
<p>However, salmon recommends transcriptome file for assembly which are not available for viruses. Virus genome are available as GenBank or GFF3 format from NCBI. Is there any way I can concatenate these formats into the format that can be used by salmon? Or is there any way around to use virus genome as reference in salmon?</p>
<hr />
<p>Citing the website:</p>
<p>Salmon is a tool for quantifying the expression of transcripts using RNA-seq data. Salmon uses new algorithms (specifically, coupling the concept of quasi-mapping with a two-phase inference procedure) to provide accurate expression estimates very quickly (i.e. wicked-fast) and while using little memory.</p>
<p>Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., &amp; Kingsford, C. (2017). Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods.</p>

CC BY-SA 4.0
2019-03-27T13:12:35.477Z
To be clear, salmon does not align reads to the genome or transcriptome *per se*, but uses *k*-mers to determine which transcript from which a read is likely derived. If you *really* need the alignments, you'll need to use a different tool. But if you're just trying to do transcript quantification, tools like salmon or kallisto are MUCH faster and just as accurate as alignment-based tools.
Daniel Standage
<rna-seq><covid-19><salmon><virus>
RNA-seq analysis of mixed viral/host reads with salmon
# RNA-seq analysis of mixed viral/host reads with salmon

(Asked by: username_0 on 2019-03-24)

I did RNA-seq of mammalian cells infected with pox virus. Now, I have read files which contain both host and virus reads. I want to align the reads both to host and viral genome. I was thinking I could concatenate the host and virus genome into one file and run [Salmon](https://combine-lab.github.io/salmon/) against this concatenated genome.

However, salmon recommends transcriptome file for assembly which are not available for viruses. Virus genome are available as GenBank or GFF3 format from NCBI. Is there any way I can concatenate these formats into the format that can be used by salmon? Or is there any way around to use virus genome as reference in salmon?

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Citing the website:

Salmon is a tool for quantifying the expression of transcripts using RNA-seq data. Salmon uses new algorithms (specifically, coupling the concept of quasi-mapping with a two-phase inference procedure) to provide accurate expression estimates very quickly (i.e. wicked-fast) and while using little memory.

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017). Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods.

**Tags:** rna-seq, covid-19, salmon, virus
> **Comments:**
> **username_1**: To be clear, salmon does not align reads to the genome or transcriptome *per se*, but uses *k*-mers to determine which transcript from which a read is likely derived. If you *really* need the alignments, you'll need to use a different tool. But if you're just trying to do transcript quantification, tools like salmon or kallisto are MUCH faster and just as accurate as alignment-based tools.  

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## 1 answers

### Answer by username_2 on 2019-03-24. Score: 2

You provide Salmon with a transcriptome fasta... so merging the human transcriptome with the pox virus genome fasta file should work. You don't mention that in your post but the viral genome should exist as a fasta. You can extract the sequences from genbank or maybe you can find our virus here: <https://www.ebi.ac.uk/genomes/virus.html>

You can find the coding transcriptome at the link below in the **cdna** folder.
The non-coding transcriptome is in the **ncrna**. You should probably merge them:

<ftp://ftp.ensembl.org/pub/release-95/fasta/homo_sapiens/>

> **Comments:**
> **username_0**: Yes, I have virus genome in fasta format. I was wondering if I just concatenate in plain fasta format , the features will be missed. How do I merge so that I will have virus features included in the merged file ?  Thank you.  
> **username_2**: If you want the virus features then you would need to find the ORF/CDS regions and subset your original fasta. You could try something like: https://www.ncbi.nlm.nih.gov/orffinder/ if they are not annotated. Alternatively they might already be present in Genbank/NCBI so you could just download them from there - although I'm not familiar enough with this to tell you how to do it in a high-throughput manner.  

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