code: def _run_variantcall_batch_multicore(items, regions, final_file):
      
      batch_name = _get_batch_name(items)
      variantcaller = _get_batch_variantcaller(items)
      work_bams = [dd.get_work_bam(d) or dd.get_align_bam(d) for d in items]
      def split_fn(data):
          out = []
          for region in regions:
              region = _region_to_coords(region)
              chrom, start, end = region
              region_str = "_".join(str(x) for x in region)
              out_file = os.path.join(dd.get_work_dir(items[0]), variantcaller, chrom,
                                      "%s-%s.vcf.gz" % (batch_name, region_str))
              out.append((region, work_bams, out_file))
          return final_file, out
      parallel = {"type": "local", "num_jobs": dd.get_num_cores(items[0]), "cores_per_job": 1}
      run_parallel = dmulti.runner(parallel, items[0]["config"])
      to_run = copy.deepcopy(items[0])
      to_run["sam_ref"] = dd.get_ref_file(to_run)
      to_run["group_orig"] = items
      parallel_split_combine([[to_run]], split_fn, run_parallel,
                             "variantcall_sample", "concat_variant_files",
                             "vrn_file", ["region", "sam_ref", "config"])
      return final_file
docs: Run variant calling on a batch of items using multiple cores.