comparison cummerbund_to_tabular.py @ 0:21d03c46f286 draft default tip

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author devteam
date Thu, 02 Apr 2015 16:13:37 -0400
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-1:000000000000 0:21d03c46f286
1 import os
2 import argparse
3 import sys
4 import string
5 import sqlite3
6
7 import logging
8
9
10 class CummerbundParser(object):
11
12 def __init__(self, opts):
13 self.cummerbund_db = opts.filename
14 self.session = sqlite3.connect( os.path.abspath( self.cummerbund_db ) )
15
16 def generate_file( self, table ):
17 if hasattr( self, table ):
18 with open( '%s.tabular' % table, 'w' ) as self.fh:
19 getattr( self, table )()
20 else:
21 print 'Table %s is not supported or does not exist.' % table
22
23 def __write_line(self, line):
24 columns = []
25 for col in line:
26 if isinstance( col, float ):
27 if str( col ) in [ '-inf', 'inf' ]:
28 columns.append( str( col ) )
29 elif col == int(col):
30 columns.append( str( int( col ) ) )
31 else:
32 columns.append( str( col ) )
33 elif col is None:
34 columns.append( '-' )
35 else:
36 columns.append( str( col ) )
37 print >>self.fh, '\t'.join( columns )
38
39 def __get_diff_from_table( self, table, identifier ):
40 columns = [ '${table}.${identifier}', '${table}.gene_id', 'genes.gene_short_name', 'genes.locus',
41 '${table}.sample_1', '${table}.sample_2', '${table}.status',
42 '${table}.value_1', '${table}.value_2', '${table}.JS_dist',
43 '${table}.test_stat', '${table}.p_value', '${table}.q_value',
44 '${table}.significant' ]
45 query = string.Template( 'SELECT %s FROM ${table} JOIN genes on ${table}.gene_id = genes.gene_id' % ', '.join(columns) )
46 result = self.session.execute( query.safe_substitute( table=table, identifier=identifier ) )
47 self.__write_line( [ 'test_id', 'gene_id', 'gene', 'locus', 'sample_1',
48 'sample_2', 'status', 'value_1', 'value_2', 'sqrt(JS)',
49 'test_stat', 'p_value', 'q_value', 'significant' ] )
50 for row in result:
51 self.__write_line( row )
52
53 def __get_read_group_data( self, table, identifier ):
54 header = [ 'tracking_id', 'condition', 'replicate', 'raw_frags',
55 'internal_scaled_frags', 'external_scaled_frags', 'FPKM',
56 'effective_length', 'status' ]
57 columns = [ identifier, 'sample_name', 'replicate', 'raw_frags',
58 'internal_scaled_frags', 'external_scaled_frags', 'fpkm',
59 'effective_length', 'status' ]
60 self.__write_line( header )
61 for row in self.session.execute( 'SELECT %s FROM %s' % ( ', '.join( columns ), table ) ):
62 self.__write_line( row )
63
64
65 def __get_exp_diff( self, table, data_table, data_table_as, column ):
66 header = [ 'test_id', 'gene_id', 'gene', 'locus', 'sample_1', 'sample_2',
67 'status', 'value_1', 'value_2', 'log2(fold_change)', 'test_stat',
68 'p_value', 'q_value', 'significant' ]
69 columns = [ '${dtas}.${column}', '${table}.gene_id', '${table}.gene_short_name', '${table}.locus',
70 '${dtas}.sample_1', '${dtas}.sample_2', '${dtas}.status',
71 '${dtas}.value_1', '${dtas}.value_2', '${dtas}.log2_fold_change',
72 '${dtas}.test_stat', '${dtas}.p_value', '${dtas}.q_value',
73 '${dtas}.significant' ]
74 query = string.Template( 'SELECT %s FROM ${dtab} as ${dtas} JOIN ${table} on ${dtas}.${column} = ${table}.${column}' % ', '.join( columns ) )
75 self.__write_line( header )
76 for row in self.session.execute( query.safe_substitute( dtas=data_table_as, dtab=data_table, table=table, column=column ) ):
77 self.__write_line( row )
78
79 def __get_per_sample_fpkm( self, identifiers, table, column ):
80 columns = []
81 for identifier in identifiers:
82 samples = self.session.execute( "SELECT sample_name FROM %s WHERE %s = '%s' ORDER BY sample_name ASC" % ( table, column, identifier[0] ) )
83 for sample in samples:
84 sample_name = sample[0]
85 columns.extend( [ '%s_FPKM' % sample_name,
86 '%s_conf_lo' % sample_name,
87 '%s_conf_hi' % sample_name,
88 '%s_status' % sample_name ] )
89 return columns
90
91 def __get_fpkms( self, table, data_table, column ):
92 tss_columns = [ column, 'class_code', 'nearest_ref_id', 'gene_id',
93 'gene_short_name', column, 'locus', 'length', 'coverage' ]
94 output_cols = [ 'tracking_id', 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name',
95 'tss_id', 'locus', 'length', 'coverage' ]
96 tss_groups = self.session.execute( 'SELECT %s FROM %s LIMIT 1' % ( ', '.join( tss_columns ), table ) )
97 output_cols.extend( self.__get_per_sample_fpkm( identifiers=tss_groups, column=column, table=data_table ) )
98 self.__write_line( output_cols )
99 tss_groups = self.session.execute( 'SELECT %s FROM %s' % ( ', '.join( tss_columns ), table ) )
100 for tss_group in tss_groups:
101 out_data = list( tss_group )
102 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] ) )
103 for sample in samples:
104 out_data.extend( list( sample ) )
105 self.__write_line( out_data )
106
107 def __get_count_data( self, table, column ):
108 output_cols = [ 'tracking_id' ]
109 tss_groups = self.session.execute( 'SELECT %s FROM %s LIMIT 1' % ( column, table ) )
110 output_cols.extend( self.__get_per_sample_count_cols( identifiers=tss_groups, table=table, column=column ) )
111 self.__write_line( output_cols )
112 self.__get_per_sample_count_data( table=table, column=column )
113
114 def __get_per_sample_count_data( self, table, column ):
115 result = self.session.execute( 'SELECT DISTINCT(%s) FROM %s' % ( column, table ) )
116 for row in result:
117 isoform_id = row[0]
118 output_data = [ isoform_id ]
119 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 ) )
120 for samplerow in per_sample:
121 output_data.extend( list( samplerow ) )
122 self.__write_line( output_data )
123
124 def __get_per_sample_count_cols( self, identifiers, table, column ):
125 columns = []
126 for identifier in identifiers:
127 samples = self.session.execute( "SELECT sample_name FROM %s WHERE %s = '%s' ORDER BY sample_name ASC" % ( table, column, identifier[0] ) )
128 for sample in samples:
129 sample_name = sample[0]
130 columns.extend( [ '%s_count' % sample_name,
131 '%s_count_variance' % sample_name,
132 '%s_count_uncertainty_var' % sample_name,
133 '%s_count_dispersion_var' % sample_name,
134 '%s_status' % sample_name ] )
135 return columns
136
137 def splicing_diff( self ):
138 self.__get_diff_from_table( 'splicingDiffData', 'TSS_group_id' )
139
140 def promoters_diff( self ):
141 self.__get_diff_from_table( 'promoterDiffData', 'gene_id' )
142
143 def cds_diff( self ):
144 self.__get_diff_from_table( 'CDSDiffData', 'gene_id' )
145
146 def tss_fpkm( self ):
147 data_table = 'TSSData'
148 table = 'TSS'
149 column = 'TSS_group_id'
150 self.__get_fpkms( data_table=data_table, table=table, column=column )
151
152 def isoform_fpkm( self ):
153 data_table = 'isoformData'
154 table = 'isoforms'
155 column = 'isoform_id'
156 self.__get_fpkms( data_table=data_table, table=table, column=column )
157
158 def genes_fpkm( self ):
159 output_cols = [ 'tracking_id', 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name',
160 'tss_id', 'locus', 'length', 'coverage' ]
161 iso_groups = self.session.execute( 'SELECT gene_id FROM genes LIMIT 1' )
162 output_cols.extend( self.__get_per_sample_fpkm( identifiers=iso_groups, column='gene_id', table='geneData' ) )
163 self.__write_line( output_cols )
164 data_columns = [ 'genes.gene_id', 'genes.class_code', 'genes.nearest_ref_id', 'genes.gene_id', 'genes.gene_short_name',
165 'GROUP_CONCAT(TSS.TSS_group_id)', 'genes.locus', 'genes.length', 'genes.coverage' ]
166 query = 'SELECT %s FROM genes JOIN TSS on TSS.gene_id = genes.gene_id GROUP BY genes.gene_id' % ', '.join( data_columns )
167 result = self.session.execute( query )
168 for row in result:
169 gene_id = row[0]
170 output_data = list( row )
171 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 )
172 for samplerow in per_sample:
173 output_data.extend( list( samplerow ) )
174 self.__write_line( output_data )
175
176 def cds_fpkm( self ):
177 output_cols = [ 'tracking_id', 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name',
178 'tss_id', 'locus', 'length', 'coverage' ]
179 iso_groups = self.session.execute( 'SELECT CDS_id FROM CDS LIMIT 1' )
180 output_cols.extend( self.__get_per_sample_fpkm( identifiers=iso_groups, column='CDS_id', table='CDSData' ) )
181 self.__write_line( output_cols )
182 data_columns = [ 'CDS_id', 'class_code', 'nearest_ref_id', 'gene_id', 'gene_short_name',
183 'GROUP_CONCAT(TSS_group_id)', 'locus', 'length', 'coverage' ]
184 query = 'SELECT %s FROM CDS GROUP BY CDS_id' % ', '.join( data_columns )
185 result = self.session.execute( query )
186 for row in result:
187 CDS_id = row[0]
188 output_data = list( row )
189 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 )
190 for samplerow in per_sample:
191 output_data.extend( list( samplerow ) )
192 self.__write_line( output_data )
193
194 def tss_count_tracking( self ):
195 self.__get_count_data( table='TSSCount', column='TSS_group_id' )
196
197 def isoform_count( self ):
198 self.__get_count_data( table='isoformCount', column='isoform_id' )
199
200 def genes_count( self ):
201 self.__get_count_data( table='geneCount', column='gene_id' )
202
203 def cds_count( self ):
204 self.__get_count_data( table='CDSCount', column='CDS_id' )
205
206 def tss_group_exp( self ):
207 columns = [ 'TEDD.TSS_group_id', 'TSS.gene_id', 'TSS.gene_short_name', 'TSS.locus',
208 'TEDD.sample_1', 'TEDD.sample_2', 'TEDD.status',
209 'TEDD.value_1', 'TEDD.value_2', 'TEDD.log2_fold_change',
210 'TEDD.test_stat', 'TEDD.p_value', 'TEDD.q_value', 'TEDD.significant' ]
211 query = [ 'SELECT %s FROM TSSExpDiffData AS TEDD' % ', '.join(columns),
212 'JOIN TSS on TEDD.TSS_group_id = TSS.TSS_group_id' ]
213 self.__write_line( [ 'test_id', 'gene_id', 'gene', 'locus',
214 'sample_1', 'sample_2', 'status', 'value_1',
215 'value_2', 'log2(fold_change)', 'test_stat',
216 'p_value', 'q_value', 'significant' ] )
217 for row in self.session.execute( ' '.join( query ) ):
218 self.__write_line( row )
219
220 def run_info( self ):
221 self.__write_line( [ 'param', 'value' ] )
222 for row in self.session.execute( 'SELECT param, value FROM runInfo' ):
223 self.__write_line( row )
224
225 def read_groups( self ):
226 self.__write_line( [ 'file', 'condition', 'replicate_num', 'total_mass', 'norm_mass', 'internal_scale', 'external_scale' ] )
227 for row in self.session.execute( 'SELECT file, sample_name, replicate, total_mass, norm_mass, internal_scale, external_scale FROM replicates' ):
228 self.__write_line( row )
229
230 def isoform_exp_diff( self ):
231 self.__get_exp_diff( table='isoforms', data_table='isoformExpDiffData', data_table_as='iED', column='isoform_id' )
232
233 def gene_exp_diff( self ):
234 self.__get_exp_diff( table='genes', data_table='geneExpDiffData', data_table_as='gEDD', column='gene_id' )
235
236 def cds_exp_diff( self ):
237 self.__get_exp_diff( table='CDS', data_table='CDSExpDiffData', data_table_as='CED', column='CDS_id' )
238
239 def tss_rg( self ):
240 self.__get_read_group_data( table='TSSReplicateData', identifier='TSS_group_id' )
241
242 def isoform_rg( self ):
243 self.__get_read_group_data( table='isoformReplicateData', identifier='isoform_id' )
244
245 def gene_rg( self ):
246 self.__get_read_group_data( table='geneReplicateData', identifier='gene_id' )
247
248 def cds_rg( self ):
249 self.__get_read_group_data( table='CDSReplicateData', identifier='CDS_id' )
250
251 def var_model( self ):
252 header = [ 'condition', 'locus', 'compatible_count_mean', 'compatible_count_var', 'total_count_mean', 'total_count_var', 'fitted_var' ]
253 self.__write_line( header )
254 for row in self.session.execute( 'SELECT %s FROM varModel' % ', '.join( header ) ):
255 self.__write_line( row )
256
257 if __name__ == '__main__':
258 parser = argparse.ArgumentParser()
259 parser.add_argument( '--file', dest='filename' )
260 parser.add_argument( '--tables', dest='tables', action='append' )
261 opts = parser.parse_args()
262 cb = CummerbundParser( opts )
263 for table in opts.tables:
264 cb.generate_file( table )