<p>The best way to approach it would be to take trimmed reads map them to the bins (i.e. with bowtie2) and estimate the abundance of each bin with samtools by getting the depth of coverage:</p>
<p><a href="https://www.metagenomics.wiki/tools/samtools/breadth-of-coverage" rel="nofollow noreferrer">https://www.metagenomics.wiki/tools/samtools/breadth-of-coverage</a></p>
<p>or you can use QUANT_BIN module from the METAWRAP to do it for you. Follow this for the METAWRAP approach:</p>
<p><a href="https://github.com/bxlab/metaWRAP/issues/40" rel="nofollow noreferrer">https://github.com/bxlab/metaWRAP/issues/40</a></p>

CC BY-SA 4.0
2021-09-21T09:51:40.440Z
2021-09-21T09:51:40.440Z
Avamys
<p>I have a metagenomic dataset across multiple samples that has been grouped and binned (we did this due to poor sequence quallity).</p>
<p>It is several samples taken from termite guts of differing castes, the samples have been grouped to make binning easier due to poor sequence suitability. They have been binned via ASVs, assembling reads from all samples to generate the putative bacterial species. So I have fasta files of putative species that have been annotated via prodigal. I want to now calculate the abundance of each bin in a given sample. I think the best way to do this would be at the gene level by looking at the number of reads that map to a gene in any given sample. I am just unsure how to do this.</p>
<p>I have annotated the bins and now want to calculate the abundance of each bin in a sample but looking at the number of reads from a sample that map to each gene in a bin.</p>
<p>Is this a viable method? If so how would I do it and if not what else could I do?</p>

<genome><metagenome>
How to calculate coverage depth of genes in an annotated sequence?
# How to calculate coverage depth of genes in an annotated sequence?

(Asked by: username_0 on 2020-01-29)

I have a metagenomic dataset across multiple samples that has been grouped and binned (we did this due to poor sequence quallity).

It is several samples taken from termite guts of differing castes, the samples have been grouped to make binning easier due to poor sequence suitability. They have been binned via ASVs, assembling reads from all samples to generate the putative bacterial species. So I have fasta files of putative species that have been annotated via prodigal. I want to now calculate the abundance of each bin in a given sample. I think the best way to do this would be at the gene level by looking at the number of reads that map to a gene in any given sample. I am just unsure how to do this.

I have annotated the bins and now want to calculate the abundance of each bin in a sample but looking at the number of reads from a sample that map to each gene in a bin.

Is this a viable method? If so how would I do it and if not what else could I do?

**Tags:** genome, metagenome

---

## 1 answers

### Answer by username_1 on 2021-09-21. Score: 1

The best way to approach it would be to take trimmed reads map them to the bins (i.e. with bowtie2) and estimate the abundance of each bin with samtools by getting the depth of coverage:

<https://www.metagenomics.wiki/tools/samtools/breadth-of-coverage>

or you can use QUANT\_BIN module from the METAWRAP to do it for you. Follow this for the METAWRAP approach:

<https://github.com/bxlab/metaWRAP/issues/40>


---

