def run_star(job, fastqs, univ_options, star_options):
    """
    This module uses STAR to align the RNA fastqs to the reference

    ARGUMENTS
    1. fastqs: REFER RETURN VALUE of run_cutadapt()
    2. univ_options: Dict of universal arguments used by almost all tools
         univ_options
              +- 'dockerhub': <dockerhub to use>
    3. star_options: Dict of parameters specific to STAR
         star_options
             |- 'index_tar': <JSid for the STAR index tarball>
             +- 'n': <number of threads to allocate>
    RETURN VALUES
    1. output_files: Dict of aligned bams
         output_files
             |- 'rnaAligned.toTranscriptome.out.bam': <JSid>
             +- 'rnaAligned.sortedByCoord.out.bam': Dict of genome bam + bai
                                |- 'rna_fix_pg_sorted.bam': <JSid>
                                +- 'rna_fix_pg_sorted.bam.bai': <JSid>

    This module corresponds to node 9 on the tree
    """
    assert star_options['type'] in ('star', 'starlong')
    job.fileStore.logToMaster('Running STAR on %s' %univ_options['patient'])
    work_dir = job.fileStore.getLocalTempDir()
    input_files = {
        'rna_cutadapt_1.fastq': fastqs['rna_cutadapt_1.fastq'],
        'rna_cutadapt_2.fastq': fastqs['rna_cutadapt_2.fastq'],
        'star_index.tar.gz': star_options['index_tar']}
    input_files = get_files_from_filestore(job, input_files, work_dir,
                                           docker=True)
    parameters = ['--runThreadN', str(star_options['n']),
                  '--genomeDir', input_files['star_index'],
                  '--outFileNamePrefix', 'rna',
                  '--readFilesIn',
                  input_files['rna_cutadapt_1.fastq'],
                  input_files['rna_cutadapt_2.fastq'],
                  '--outSAMattributes', 'NH', 'HI', 'AS', 'NM', 'MD',
                  '--outSAMtype', 'BAM', 'SortedByCoordinate',
                  '--quantMode', 'TranscriptomeSAM',
                  '--outSAMunmapped', 'Within']
    if star_options['type'] == 'star':
        docker_call(tool='star', tool_parameters=parameters, work_dir=work_dir,
                    dockerhub=univ_options['dockerhub'])
    else:
        docker_call(tool='starlong', tool_parameters=parameters, work_dir=work_dir,
                    dockerhub=univ_options['dockerhub'])
    output_files = defaultdict()
    for bam_file in ['rnaAligned.toTranscriptome.out.bam',
                     'rnaAligned.sortedByCoord.out.bam']:
        output_files[bam_file] = job.fileStore.writeGlobalFile('/'.join([
            work_dir, bam_file]))
    job.fileStore.deleteGlobalFile(fastqs['rna_cutadapt_1.fastq'])
    job.fileStore.deleteGlobalFile(fastqs['rna_cutadapt_2.fastq'])
    index_star = job.wrapJobFn(index_bamfile,
                               output_files['rnaAligned.sortedByCoord.out.bam'],
                               'rna', univ_options, disk='120G')
    job.addChild(index_star)
    output_files['rnaAligned.sortedByCoord.out.bam'] = index_star.rv()
    return output_files