__init__.py 文件源码

def run(self):
        def load_evals(tx_mode):
            """Loads the error tracks from the database"""
            cds_table = tools.sqlInterface.tables['CDS'][tx_mode]['evaluation']
            mrna_table = tools.sqlInterface.tables['mRNA'][tx_mode]['evaluation']
            cds_df = pd.read_sql_table(cds_table.__tablename__, engine).set_index('AlignmentId')
            mrna_df = pd.read_sql_table(mrna_table.__tablename__, engine).set_index('AlignmentId')
            return {'CDS': cds_df, 'mRNA': mrna_df}

        pipeline_args = self.get_pipeline_args()
        track, trackdb = self.output()
        chrom_sizes = GenomeFiles.get_args(pipeline_args, self.genome).sizes
        engine = tools.sqlInterface.create_engine('sqlite:///' + pipeline_args.dbs[self.genome])
        evals = {tx_mode: load_evals(tx_mode) for tx_mode in self.tx_modes}
        consensus_args = Consensus.get_args(pipeline_args, self.genome)
        consensus_gp_info = pd.read_csv(consensus_args.consensus_gp_info, sep='\t',
                                        header=0, na_filter=False).set_index('transcript_id')
        aln_ids = set(consensus_gp_info.alignment_id)
        rows = []
        for aln_id in aln_ids:
            tx_mode = tools.nameConversions.alignment_type(aln_id)
            if tx_mode not in ['transMap', 'augTM', 'augTMR']:
                continue
            mode = 'CDS'
            df = tools.misc.slice_df(evals[tx_mode][mode], aln_id)
            if len(df) == 0:
                mode = 'mRNA'
                df = tools.misc.slice_df(evals[tx_mode][mode], aln_id)
            for tx_id, s in df.iterrows():
                bed = s.tolist()
                bed[3] = '/'.join([tx_id, bed[3], mode])
                rows.append(bed)

        tmp = luigi.LocalTarget(is_tmp=True)
        with tmp.open('w') as tmp_handle:
            tools.fileOps.print_rows(tmp_handle, rows)
        tools.procOps.run_proc(['bedSort', tmp.path, tmp.path])
        with track.open('w') as outf:
            cmd = ['bedToBigBed', '-type=bed12', '-tab', tmp.path, chrom_sizes, '/dev/stdout']
            tools.procOps.run_proc(cmd, stdout=outf, stderr='/dev/null')

        with trackdb.open('w') as outf:
            outf.write(error_template.format(genome=self.genome, path=os.path.basename(track.path)))