def _depth_to_seq2cov(input_fpath, output_fpath, sample_name):
    """Args:
        input_fpath: output of "mosdepth":
            chr22           14250   15500   name3   5.54
            chrM            100     1000    name1   916.08

        output_fpath: path to write results - input for Seq2C's cov2lr.pl, e.g.:
            seq2cov:
            chr20_tumor_1   DEFB125   chr20   68346   68413   Amplicon    68   28.0
            chr20_tumor_1   DEFB125   chr20   76641   77301   Amplicon    661  24.0
            chr20_tumor_1   DEFB125   chr20   68346   77301   Whole-Gene  729  24.3731138546

        sample_name:
            sample name (e.g. chr20_tumor_1)
    """
    # First round: collecting gene ends
    gene_end_by_gene = defaultdict(lambda: -1)
    with utils.open_gzipsafe(input_fpath) as f:
        for xs in (l.rstrip().split() for l in f if not l.startswith("#")):
            xs = [x for x in xs if x.strip()]
            if any(x == "." for x in xs): continue
            end = int(xs[2])
            gene_name = xs[3]
            gene_end_by_gene[gene_name] = max(gene_end_by_gene[gene_name], end)

    # Second round: calculating gene level coverage, and writing file for Seq2C
    total_cov_by_gene = dict()
    gene_start_by_gene = dict()
    total_size_by_gene = dict()

    with utils.open_gzipsafe(input_fpath) as f, open(output_fpath, 'w') as out:
        for xs in (l.rstrip().split() for l in f if not l.startswith("#")):
            xs = [x for x in xs if x.strip()]
            if any(x == "." for x in xs): continue
            chrom, start, end, gene_name = xs[:4]
            start, end = int(start), int(end)
            ave_depth = float(xs[-1])

            if gene_name not in gene_start_by_gene:
                gene_start_by_gene[gene_name] = start
                total_cov_by_gene[gene_name] = 0
                total_size_by_gene[gene_name] = 0
            else:
                gene_start_by_gene[gene_name] = min(start, gene_start_by_gene[gene_name])
            total_cov_by_gene[gene_name] += ave_depth * (end - start)
            total_size_by_gene[gene_name] += end - start

            fs = [sample_name, gene_name, chrom, str(start + 1), str(end), 'Amplicon', str(end - start), str(ave_depth)]
            out.write('\t'.join(fs) + '\n')

            if end >= gene_end_by_gene[gene_name]:
                assert end == gene_end_by_gene[gene_name], (end, gene_end_by_gene[gene_name])
                start = gene_start_by_gene[gene_name]
                ave_depth = total_cov_by_gene[gene_name] / total_size_by_gene[gene_name]
                size = total_size_by_gene[gene_name]
                fs = [sample_name, gene_name, chrom, str(start + 1), str(end), 'Whole-Gene', str(size), str(ave_depth)]
                out.write('\t'.join(fs) + '\n')
    return output_fpath
Args:
        input_fpath: output of "mosdepth":
            chr22           14250   15500   name3   5.54
            chrM            100     1000    name1   916.08

        output_fpath: path to write results - input for Seq2C's cov2lr.pl, e.g.:
            seq2cov:
            chr20_tumor_1   DEFB125   chr20   68346   68413   Amplicon    68   28.0
            chr20_tumor_1   DEFB125   chr20   76641   77301   Amplicon    661  24.0
            chr20_tumor_1   DEFB125   chr20   68346   77301   Whole-Gene  729  24.3731138546

        sample_name:
            sample name (e.g. chr20_tumor_1)