To calculate the average coverage and average depth for an Oxford Nanopore (ONT) sequencing run, note that these terms are often used interchangeably in genomics, where depth refers to the average number of times each base in the genome is sequenced (i.e., average coverage). You will need a reference genome or an estimate of the genome size. If you lack a reference, a rough estimate is total sequenced bases divided by genome size, but for accurate values, align the reads first.

Assuming you have FASTQ files from the ONT run, follow this pipeline:

1. Align the reads to your reference genome using minimap2, which is suitable for long reads.

minimap2 -a -x map-ont reference.fasta reads.fastq > aligned.sam

1. Convert the SAM to BAM, sort, and index it with samtools.

samtools view -bS aligned.sam > aligned.bam
samtools sort aligned.bam -o aligned.sorted.bam
samtools index aligned.sorted.bam

1. Calculate coverage and depth using mosdepth for genome-wide averages (install via conda if needed: conda install -c bioconda mosdepth). It outputs a summary file with mean depth.

mosdepth -n aligned aligned.sorted.bam
cat aligned.mosdepth.summary.txt

The last line of the summary file gives the genome-wide mean, min, and max depth.

Alternatively, use samtools coverage for per-contig statistics, then compute the overall average manually if required.

samtools coverage aligned.sorted.bam

For quality control, NanoPlot can provide additional read statistics, including estimated coverage if you supply the genome size.

NanoPlot --fastq reads.fastq --loglength -o nanoplot_output

Provide more details on your data (e.g., species, genome size) for tailored advice.

Kevin