Mercurial > repos > devteam > cummerbund_to_tabular
view cummerbund_to_tabular.py @ 0:21d03c46f286 draft default tip
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author | devteam |
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date | Thu, 02 Apr 2015 16:13:37 -0400 |
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import os import argparse import sys import string import sqlite3 import logging class CummerbundParser(object): def __init__(self, opts): self.cummerbund_db = opts.filename self.session = sqlite3.connect( os.path.abspath( self.cummerbund_db ) ) def generate_file( self, table ): if hasattr( self, table ): with open( '%s.tabular' % table, 'w' ) as self.fh: getattr( self, table )() else: print 'Table %s is not supported or does not exist.' % table def __write_line(self, line): columns = [] for col in line: if isinstance( col, float ): if str( col ) in [ '-inf', 'inf' ]: columns.append( str( col ) ) elif col == int(col): columns.append( str( int( col ) ) ) else: columns.append( str( col ) ) elif col is None: columns.append( '-' ) else: columns.append( str( col ) ) print >>self.fh, '\t'.join( columns ) def __get_diff_from_table( self, table, identifier ): columns = [ '${table}.${identifier}', '${table}.gene_id', 'genes.gene_short_name', 'genes.locus', '${table}.sample_1', '${table}.sample_2', '${table}.status', '${table}.value_1', '${table}.value_2', '${table}.JS_dist', '${table}.test_stat', '${table}.p_value', '${table}.q_value', '${table}.significant' ] query = string.Template( 'SELECT %s FROM ${table} JOIN genes on ${table}.gene_id = genes.gene_id' % ', '.join(columns) ) result = self.session.execute( query.safe_substitute( table=table, identifier=identifier ) ) self.__write_line( [ 'test_id', 'gene_id', 'gene', 'locus', 'sample_1', 'sample_2', 'status', 'value_1', 'value_2', 'sqrt(JS)', 'test_stat', 'p_value', 'q_value', 'significant' ] ) for row in result: self.__write_line( row ) def __get_read_group_data( self, table, identifier ): header = [ 'tracking_id', 'condition', 'replicate', 'raw_frags', 'internal_scaled_frags', 'external_scaled_frags', 'FPKM', 'effective_length', 'status' ] columns = [ identifier, 'sample_name', 'replicate', 'raw_frags', 'internal_scaled_frags', 'external_scaled_frags', 'fpkm', 'effective_length', 'status' ] self.__write_line( header ) for row in self.session.execute( 'SELECT %s FROM %s' % ( ', '.join( columns ), table ) ): self.__write_line( row ) def __get_exp_diff( self, table, data_table, data_table_as, column ): header = [ 'test_id', 'gene_id', 'gene', 'locus', 'sample_1', 'sample_2', 'status', 'value_1', 'value_2', 'log2(fold_change)', 'test_stat', 'p_value', 'q_value', 'significant' ] columns = [ '${dtas}.${column}', '${table}.gene_id', '${table}.gene_short_name', '${table}.locus', '${dtas}.sample_1', '${dtas}.sample_2', '${dtas}.status', '${dtas}.value_1', '${dtas}.value_2', '${dtas}.log2_fold_change', '${dtas}.test_stat', '${dtas}.p_value', '${dtas}.q_value', '${dtas}.significant' ] query = string.Template( 'SELECT %s FROM ${dtab} as ${dtas} JOIN ${table} on ${dtas}.${column} = ${table}.${column}' % ', '.join( columns ) ) self.__write_line( header ) for row in self.session.execute( query.safe_substitute( dtas=data_table_as, dtab=data_table, table=table, column=column ) ): self.__write_line( row ) def __get_per_sample_fpkm( self, identifiers, table, column ): columns = [] for identifier in identifiers: samples = self.session.execute( "SELECT sample_name FROM %s WHERE %s = '%s' ORDER BY sample_name ASC" % ( table, column, identifier[0] ) ) for sample in samples: sample_name = sample[0] columns.extend( [ '%s_FPKM' % sample_name, '%s_conf_lo' % sample_name, '%s_conf_hi' % sample_name, '%s_status' % sample_name ] ) return columns def __get_fpkms( self, table, data_table, column ): tss_columns = [ column, 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name', column, 'locus', 'length', 'coverage' ] output_cols = [ 'tracking_id', 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name', 'tss_id', 'locus', 'length', 'coverage' ] tss_groups = self.session.execute( 'SELECT %s FROM %s LIMIT 1' % ( ', '.join( tss_columns ), table ) ) output_cols.extend( self.__get_per_sample_fpkm( identifiers=tss_groups, column=column, table=data_table ) ) self.__write_line( output_cols ) tss_groups = self.session.execute( 'SELECT %s FROM %s' % ( ', '.join( tss_columns ), table ) ) for tss_group in tss_groups: out_data = list( tss_group ) samples = self.session.execute( "SELECT fpkm, conf_hi, conf_lo, quant_status FROM %s WHERE %s = '%s' ORDER BY sample_name ASC" % ( data_table, column, tss_group[0] ) ) for sample in samples: out_data.extend( list( sample ) ) self.__write_line( out_data ) def __get_count_data( self, table, column ): output_cols = [ 'tracking_id' ] tss_groups = self.session.execute( 'SELECT %s FROM %s LIMIT 1' % ( column, table ) ) output_cols.extend( self.__get_per_sample_count_cols( identifiers=tss_groups, table=table, column=column ) ) self.__write_line( output_cols ) self.__get_per_sample_count_data( table=table, column=column ) def __get_per_sample_count_data( self, table, column ): result = self.session.execute( 'SELECT DISTINCT(%s) FROM %s' % ( column, table ) ) for row in result: isoform_id = row[0] output_data = [ isoform_id ] per_sample = self.session.execute( "SELECT count, variance, uncertainty, dispersion, status FROM %s WHERE %s = '%s' ORDER BY sample_name ASC" % ( table, column, isoform_id ) ) for samplerow in per_sample: output_data.extend( list( samplerow ) ) self.__write_line( output_data ) def __get_per_sample_count_cols( self, identifiers, table, column ): columns = [] for identifier in identifiers: samples = self.session.execute( "SELECT sample_name FROM %s WHERE %s = '%s' ORDER BY sample_name ASC" % ( table, column, identifier[0] ) ) for sample in samples: sample_name = sample[0] columns.extend( [ '%s_count' % sample_name, '%s_count_variance' % sample_name, '%s_count_uncertainty_var' % sample_name, '%s_count_dispersion_var' % sample_name, '%s_status' % sample_name ] ) return columns def splicing_diff( self ): self.__get_diff_from_table( 'splicingDiffData', 'TSS_group_id' ) def promoters_diff( self ): self.__get_diff_from_table( 'promoterDiffData', 'gene_id' ) def cds_diff( self ): self.__get_diff_from_table( 'CDSDiffData', 'gene_id' ) def tss_fpkm( self ): data_table = 'TSSData' table = 'TSS' column = 'TSS_group_id' self.__get_fpkms( data_table=data_table, table=table, column=column ) def isoform_fpkm( self ): data_table = 'isoformData' table = 'isoforms' column = 'isoform_id' self.__get_fpkms( data_table=data_table, table=table, column=column ) def genes_fpkm( self ): output_cols = [ 'tracking_id', 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name', 'tss_id', 'locus', 'length', 'coverage' ] iso_groups = self.session.execute( 'SELECT gene_id FROM genes LIMIT 1' ) output_cols.extend( self.__get_per_sample_fpkm( identifiers=iso_groups, column='gene_id', table='geneData' ) ) self.__write_line( output_cols ) data_columns = [ 'genes.gene_id', 'genes.class_code', 'genes.nearest_ref_id', 'genes.gene_id', 'genes.gene_short_name', 'GROUP_CONCAT(TSS.TSS_group_id)', 'genes.locus', 'genes.length', 'genes.coverage' ] query = 'SELECT %s FROM genes JOIN TSS on TSS.gene_id = genes.gene_id GROUP BY genes.gene_id' % ', '.join( data_columns ) result = self.session.execute( query ) for row in result: gene_id = row[0] output_data = list( row ) per_sample = self.session.execute( "SELECT fpkm, conf_lo, conf_hi, quant_status FROM geneData WHERE gene_id = '%s' ORDER BY sample_name ASC" % gene_id ) for samplerow in per_sample: output_data.extend( list( samplerow ) ) self.__write_line( output_data ) def cds_fpkm( self ): output_cols = [ 'tracking_id', 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name', 'tss_id', 'locus', 'length', 'coverage' ] iso_groups = self.session.execute( 'SELECT CDS_id FROM CDS LIMIT 1' ) output_cols.extend( self.__get_per_sample_fpkm( identifiers=iso_groups, column='CDS_id', table='CDSData' ) ) self.__write_line( output_cols ) data_columns = [ 'CDS_id', 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name', 'GROUP_CONCAT(TSS_group_id)', 'locus', 'length', 'coverage' ] query = 'SELECT %s FROM CDS GROUP BY CDS_id' % ', '.join( data_columns ) result = self.session.execute( query ) for row in result: CDS_id = row[0] output_data = list( row ) per_sample = self.session.execute( "SELECT fpkm, conf_lo, conf_hi, quant_status FROM CDSData WHERE CDS_id = '%s' ORDER BY sample_name ASC" % CDS_id ) for samplerow in per_sample: output_data.extend( list( samplerow ) ) self.__write_line( output_data ) def tss_count_tracking( self ): self.__get_count_data( table='TSSCount', column='TSS_group_id' ) def isoform_count( self ): self.__get_count_data( table='isoformCount', column='isoform_id' ) def genes_count( self ): self.__get_count_data( table='geneCount', column='gene_id' ) def cds_count( self ): self.__get_count_data( table='CDSCount', column='CDS_id' ) def tss_group_exp( self ): columns = [ 'TEDD.TSS_group_id', 'TSS.gene_id', 'TSS.gene_short_name', 'TSS.locus', 'TEDD.sample_1', 'TEDD.sample_2', 'TEDD.status', 'TEDD.value_1', 'TEDD.value_2', 'TEDD.log2_fold_change', 'TEDD.test_stat', 'TEDD.p_value', 'TEDD.q_value', 'TEDD.significant' ] query = [ 'SELECT %s FROM TSSExpDiffData AS TEDD' % ', '.join(columns), 'JOIN TSS on TEDD.TSS_group_id = TSS.TSS_group_id' ] self.__write_line( [ 'test_id', 'gene_id', 'gene', 'locus', 'sample_1', 'sample_2', 'status', 'value_1', 'value_2', 'log2(fold_change)', 'test_stat', 'p_value', 'q_value', 'significant' ] ) for row in self.session.execute( ' '.join( query ) ): self.__write_line( row ) def run_info( self ): self.__write_line( [ 'param', 'value' ] ) for row in self.session.execute( 'SELECT param, value FROM runInfo' ): self.__write_line( row ) def read_groups( self ): self.__write_line( [ 'file', 'condition', 'replicate_num', 'total_mass', 'norm_mass', 'internal_scale', 'external_scale' ] ) for row in self.session.execute( 'SELECT file, sample_name, replicate, total_mass, norm_mass, internal_scale, external_scale FROM replicates' ): self.__write_line( row ) def isoform_exp_diff( self ): self.__get_exp_diff( table='isoforms', data_table='isoformExpDiffData', data_table_as='iED', column='isoform_id' ) def gene_exp_diff( self ): self.__get_exp_diff( table='genes', data_table='geneExpDiffData', data_table_as='gEDD', column='gene_id' ) def cds_exp_diff( self ): self.__get_exp_diff( table='CDS', data_table='CDSExpDiffData', data_table_as='CED', column='CDS_id' ) def tss_rg( self ): self.__get_read_group_data( table='TSSReplicateData', identifier='TSS_group_id' ) def isoform_rg( self ): self.__get_read_group_data( table='isoformReplicateData', identifier='isoform_id' ) def gene_rg( self ): self.__get_read_group_data( table='geneReplicateData', identifier='gene_id' ) def cds_rg( self ): self.__get_read_group_data( table='CDSReplicateData', identifier='CDS_id' ) def var_model( self ): header = [ 'condition', 'locus', 'compatible_count_mean', 'compatible_count_var', 'total_count_mean', 'total_count_var', 'fitted_var' ] self.__write_line( header ) for row in self.session.execute( 'SELECT %s FROM varModel' % ', '.join( header ) ): self.__write_line( row ) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument( '--file', dest='filename' ) parser.add_argument( '--tables', dest='tables', action='append' ) opts = parser.parse_args() cb = CummerbundParser( opts ) for table in opts.tables: cb.generate_file( table )