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I am using a pipeline from nanopore to detect structural variants (SVs) in a human sample with long-reads sequencing. The first steps of the pipeline are:

  1. index the reference genome with minimap2
  2. map the long reads to a reference genome using same tool as above
  3. Get BED coordinates from the .bam file.

While the first two steps uses minimap, the third one uses a python script written by the developers of the pipeline, which can be found here.

After the pipeline calls bamref2bed i.e. the python script above, my target.bed looks like the following:

chr1    0   249250621
chr2    0   243199373
chr3    0   198022430
chr4    0   191154276
chr5    0   180915260
chr6    0   171115067
chr7    0   159138663
chr8    0   146364022
chr9    0   141213431
chr10   0   135534747
chr11   0   135006516
chr12   0   133851895
chr13   0   115169878
chr14   0   107349540
chr15   0   102531392
chr16   0   90354753
chr17   0   81195210
chr18   0   78077248
chr19   0   59128983
chr20   0   63025520
chr21   0   48129895
chr22   0   51304566
chrX    0   155270560
chrY    0   59373566

As far as I am concerned the first three columns of a bed file refer to (I) chr name, (II) start position (III) end position. The main thing I am wondering is how come all chromosomes have a start position of 0. Also, reading about converting bam to bed files I guess the most important feature would be the coverage across the whole chromosomes, which in this file is missing.

But my main question would be: is it normal to have a start position of 0 for all chromosomes or is there something wrong here?

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    $\begingroup$ BED intervals are usually zero-based, half-open indexed. Issues aside from whether these particular intervals are meaningful results, a starting position of 0 is entirely normal for a BED element. Cite: genome.ucsc.edu/blog/… $\endgroup$ Oct 22, 2019 at 9:12

1 Answer 1

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I cannot access the pipeline from nanopore, but looking at the python script you provided:

with pysam.AlignmentFile(bam_file, "r") as bam:
    for tid in range(0, bam.nreferences):
        ref_name = bam.get_reference_name(tid)
        if len(list(filter(lambda x: x in ref_name, filter_names))) > 0:
            continue

        print(ref_name,
              "0",
              str(bam.get_reference_length(ref_name)),
              sep='\t')

So the script gets the length of the chromosome and by default, outputs the start as 0.Zero based coordinate system is sometimes used in UCSC systems, so I am only guessing the authors of the pipeline use this convention somewhere further down.

As for the coverage you mentioned, that is usually output as a score in the 5th column (bed format). In those situations, usually the coordinates of the alignments in the bam file are converted into bed format. In this pipeline, i think the authors are simply extracting the chromosome information out and putting it into a tabular form.

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  • $\begingroup$ Thanks, that's useful information, I was not aware of the zero based coordinate system. In fact I managed to find the other .bed file with the coverage per chromosome, so I guess the .bed file that I mentioned is only displaying the chromosomes length. $\endgroup$
    – BCArg
    Oct 22, 2019 at 9:07

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