e7f828d1d1d15fe187a2cb9a241dee10874af38f mmaddren Mon Feb 6 13:35:15 2012 -0800 cvValidate updated for new cv spec diff --git python/lib/ucscgenomics/mdb.py python/lib/ucscgenomics/mdb.py index b39400a..9ab868c 100644 --- python/lib/ucscgenomics/mdb.py +++ python/lib/ucscgenomics/mdb.py @@ -1,194 +1,210 @@ from ucscgenomics import ra class DataType(object): def __init__(self, name, molecule, strategy, source, selection, type): self.name = name self.molecule = molecule self.strategy = strategy self.source = source self.selection = selection self.type = type @property def valid(self): return self.molecule != 'REPLACE' and self.strategy != 'REPLACE' and self.source != 'REPLACE' and self.selection != 'REPLACE' and self.type != None @property def shouldSubmit(self): return self.type != 'NotGeo' dataTypes = { - 'Cage': DataType('Cage', 'OVERRIDE RNA', 'OTHER', 'transcriptomic', 'CAGE', 'HighThroughput'), + 'Cage': DataType( 'Cage', 'RNA', 'OTHER', 'transcriptomic', 'CAGE', 'HighThroughput'), 'ChipSeq': DataType('ChipSeq', 'genomic DNA', 'ChIP-Seq', 'genomic', 'ChIP', 'HighThroughput'), 'DnaPet': DataType('DnaPet', 'genomic DNA', 'OTHER', 'genomic', 'size fractionation', 'HighThroughput'), 'DnaseDgf': DataType('DnaseDgf', 'genomic DNA', 'DNase-Hypersensitivity', 'genomic', 'DNase', 'HighThroughput'), 'DnaseSeq': DataType('DnaseSeq', 'genomic DNA', 'DNase-Hypersensitivity', 'genomic', 'DNase', 'HighThroughput'), 'FaireSeq': DataType('FaireSeq', 'genomic DNA', 'OTHER', 'genomic', 'other', 'HighThroughput'), 'MethylSeq': DataType('MethylSeq', 'genomic DNA', 'MRE-Seq', 'genomic', 'Restriction Digest', 'HighThroughput'), 'MethylRrbs': DataType('MethylRrbs', 'genomic DNA', 'Bisulfite-Seq', 'genomic', 'Reduced Representation', 'HighThroughput'), 'Orchid': DataType('Orchid', 'genomic DNA', 'OTHER', 'genomic', 'other', 'HighThroughput'), 'Proteogenomics': DataType('Proteogenomics', 'protein', 'mass spectrometry-based proteogenomic mapping', 'protein', 'chromatographically fractionated peptides', 'HighThroughput'), - 'RnaPet': DataType('RnaPet', 'OVERRIDE RNA', 'OTHER', 'transcriptomic', 'other', 'HighThroughput'), - 'RnaSeq': DataType('RnaSeq', 'OVERRIDE RNA', 'RNA-Seq', 'transcriptomic', 'cDNA', 'HighThroughput'), + 'RnaPet': DataType( 'RnaPet', 'RNA', 'OTHER', 'transcriptomic', 'other', 'HighThroughput'), + 'RnaSeq': DataType( 'RnaSeq', 'RNA', 'RNA-Seq', 'transcriptomic', 'cDNA', 'HighThroughput'), - #these need to be curated - '5C': DataType('5C', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), - 'AffyExonArray': DataType('AffyExonArray', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'MicroArray'), + #doublecheck + 'ChiaPet': DataType( 'ChiaPet', 'genomic DNA', 'ChIP-Seq followed by ligation', 'genomic', 'other', 'HighThroughput'), + 'Nucleosome': DataType( 'Nucleosome', 'genomic DNA', 'ChIP-Seq', 'genomic', 'ChIP', 'HighThroughput'), + 'RipSeq': DataType( 'RipSeq', 'RNA', 'OTHER', 'transcriptomic', 'RNA binding protein antibody', 'HighThroughput'), + #for ripseq, ask geo about new 'ripseq' + + #not geo stuff + '5C': DataType('5C', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo'), 'Bip': DataType('Bip', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo'), - 'Cluster': DataType('Cluster', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), - 'Cnv': DataType('Cnv', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), - 'Combined': DataType('Combined', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), - 'Genotype': DataType('Genotype', 'genomic DNA', 'REPLACE', 'REPLACE', 'REPLACE', None), 'Gencode': DataType('Gencode', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo'), - 'ChiaPet': DataType('ChiaPet', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), 'Mapability': DataType('Mapability', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo'), - 'MethylArray': DataType('MethylArray', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), 'NRE': DataType('NRE', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo'), - 'Nucleosome': DataType('Nucleosome', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), - 'RnaChip': DataType('RnaChip', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), - 'RipGeneSt': DataType('RipGeneSt', 'OVERRIDE RNA', 'REPLACE', 'transcriptomic', 'RNA binding protein antibody', 'MicroArray'), #this isn't correct - 'RipTiling': DataType('RipTiling', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), - 'RipChip': DataType('RipChip', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), - 'RipSeq': DataType('RipSeq', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), 'Switchgear': DataType('Switchgear', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo'), - 'TfbsValid': DataType('TfbsValid', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo') + 'TfbsValid': DataType('TfbsValid', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo'), + 'Cluster': DataType('Cluster', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', 'NotGeo'), + + #array + 'AffyExonArray': DataType( 'AffyExonArray', 'mRNA', 'RNA-Microarray', 'transcriptomic', 'polyA', 'MicroArray'), + 'MethylArray': DataType( 'MethylArray', 'genomic DNA', 'REPLACE', 'genomic', 'REPLACE', 'MicroArray'), + 'RipGeneSt': DataType( 'RipGeneSt', 'RNA', 'REPLACE', 'transcriptomic', 'RNA binding protein antibody', 'MicroArray'), #this isn't correct + 'RipTiling': DataType( 'RipTiling', 'RNA', 'REPLACE', 'transcriptomic', 'RNA binding protein antibody', 'MicroArray'), + + #these need to be curated + 'Cnv': DataType( 'Cnv', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), + 'Combined': DataType( 'Combined', 'REPLACE', 'REPLACE', 'REPLACE', 'REPLACE', None), + 'Genotype': DataType( 'Genotype', 'genomic DNA', 'REPLACE', 'genomic', 'REPLACE', None), + 'RnaChip': DataType( 'RnaChip', 'RNA', 'REPLACE', 'transcriptomic', 'RNA binding protein antibody', None), + 'RipChip': DataType( 'RipChip', 'RNA', 'REPLACE', 'transcriptomic', 'RNA binding protein antibody', None) + + } #compare this to the source in datatype, give GP ids depending on the type gpIds = { 'human genomic': '63443', 'human transcriptomic': '30709', 'human protein': '63447', 'mouse genomic': '63471', 'mouse transcriptomic': '66167', 'mouse protein': '63475' } class MdbFile(ra.RaFile): ''' This should be used for all files in the metaDb, since they extend RaFile with useful functionality specific to metaDb ra files. ''' @property def expVars(self): '''the experimental variables used in this track''' try: return self._expVars except AttributeError: self._expVars = self.compositeStanza['expVars'].split(',') return self._expVars @property def dataType(self): '''The data type of the experiment. 'None' if inconsistent.''' try: return self._dataType except AttributeError: self._dataType = None for e in self.experiments.itervalues(): if self._dataType == None and e.dataType != None: + print e.dataType self._dataType = e.dataType elif self._dataType != e.dataType or e.dataType == None: + print 'multiple data types!' self._dataType = None break + print 'still none' return self._dataType @property def compositeStanza(self): '''the stanza (typically first in file) describing the composite''' try: return self._compositeStanza except AttributeError: self._compositeStanza = self.filter(lambda s: s['objType'] == 'composite', lambda s: s) if len(self._compositeStanza) != 1: raise KeyError else: self._compositeStanza = self._compositeStanza[0] return self._compositeStanza @property def experiments(self): '''dictionary of MdbExp objects indexed by the expId''' try: return self._experiments except AttributeError: self._experiments = dict() exps = self.filter(lambda s: s['objType'] != 'composite', lambda s: (s['expId'], s)) stanzas = dict() for k, v in exps: if k not in stanzas: stanzas[k] = list() stanzas[k].append(v) for id in stanzas.iterkeys(): self._experiments[id] = MdbExp(id, self, stanzas[id]) return self._experiments def __init__(self, filepath): ra.RaFile.__init__(self) self.read(filepath) def readStanza(self, stanza, key=None): entry = MdbStanza(self) if entry.readStanza(stanza, key) == None: return None, None, None val1, val2 = entry.readStanza(stanza, key) return val1, val2, entry class MdbStanza(ra.RaStanza): @property def title(self): '''The expVars catted together, making the title used for GEO''' try: return self._title except AttributeError: expVars = self._parent.expVars if expVars[0] in self: self._title = self[expVars[0]].replace('-m', '') else: self._title = None for expVar in expVars[1:len(expVars)]: if expVar in self and self[expVar] != 'None': self._title += '_' + self[expVar] return self._title def __init__(self, parent): ra.RaStanza.__init__(self) self._parent = parent class MdbExp(list): ''' Describes a single experiment ID, which has a collection of its stanzas as well as some additional data that should typically be consistent across all the stanzas, as well as verifying that the data is in fact consistent. ''' @property def name(self): return self._id @property def dataType(self): '''The data type of the experiment. 'None' if inconsistent.''' try: return self._dataType except AttributeError: self._dataType = None for s in self: if 'dataType' in s: if self._dataType == None: + print dataTypes[s['dataType']] self._dataType = dataTypes[s['dataType']] elif self._dataType.name != s['dataType']: + print 'exp multiple data types!' self._dataType = None break + + print 'still none (exp)' return self._dataType def __init__(self, id, parent, stanzas): list.__init__(self) self.extend(stanzas) self._id = id self._parent = parent