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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def wrap_fusion(job, fastqs, star_output, univ_options, star_fusion_options, fusion_inspector_options):
 """ A wrapper for run_fusion using the results from cutadapt and star as input. :param tuple fastqs: RNA-Seq FASTQ Filestore IDs :param dict star_output: Dictionary containing STAR output files :param dict univ_options: universal arguments used by almost all tools :param dict star_fusion_options: STAR-Fusion specific parameters :param dict fusion_inspector_options: FusionInspector specific parameters :return: Transgene BEDPE file :rtype: toil.fileStore.FileID """

    # Give user option to skip fusion calling
    if not star_fusion_options['run']:
        job.fileStore.logToMaster('Skipping STAR-Fusion on %s' % univ_options['patient'])
        return

    fusion = job.wrapJobFn(run_fusion, fastqs, star_output['rnaChimeric.out.junction'],
                               univ_options, star_fusion_options, fusion_inspector_options,
                               cores=star_fusion_options['n'],
                               memory=PromisedRequirement(lambda x: int(1.85 * x.size),
                                                          star_fusion_options['index']),
                               disk=PromisedRequirement(fusion_disk,
                                                        fastqs,
                                                        star_fusion_options['index'])).encapsulate()
    job.addChild(fusion)
    return fusion.rv()