comparison mothur/lib/galaxy/datatypes/metagenomics.py @ 2:e990ac8a0f58

Migrated tool version 1.19.0 from old tool shed archive to new tool shed repository

1:fcc0778f6987

        finally:
            close(fh)
        return False

class SequenceTaxonomy(Tabular):
    file_ext = 'taxonomy'
    def __init__(self, **kwd):
        """A list of names"""
        Tabular.__init__( self, **kwd )
        self.column_names = ['name','taxonomy']

class ConsensusTaxonomy(Tabular):
    file_ext = 'cons.taxonomy'
    def __init__(self, **kwd):
        """A list of names"""

            fh.close()
        return False

## Qiime Classes

class MetadataMapping(Tabular):
    MetadataElement( name="column_names", default=[], desc="Column Names", readonly=False, visible=True, no_value=[] )
    file_ext = 'mapping'

    def __init__(self, **kwd):
        """
        http://qiime.sourceforge.net/documentation/file_formats.html#mapping-file-overview
        Information about the samples necessary to perform the data analysis. 

    def set_meta( self, dataset, overwrite = True, skip = None, max_data_lines = None, **kwd ):
        Tabular.set_meta(self, dataset, overwrite, skip, max_data_lines)
        self.set_column_names(dataset)

if __name__ == '__main__':
    import doctest, sys
    doctest.testmod(sys.modules[__name__])

2:e990ac8a0f58

        finally:
            close(fh)
        return False

class SequenceTaxonomy(Tabular):
    file_ext = 'seq.taxonomy'
    """
        A table with 2 columns:
        - SequenceName
        - Taxonomy (semicolon-separated taxonomy in descending order)
        Example:
          X56533.1        Eukaryota;Alveolata;Ciliophora;Intramacronucleata;Oligohymenophorea;Hymenostomatida;Tetrahymenina;Glaucomidae;Glaucoma;
          X97975.1        Eukaryota;Parabasalidea;Trichomonada;Trichomonadida;unclassified_Trichomonadida;
          AF052717.1      Eukaryota;Parabasalidea;
    """
    def __init__(self, **kwd):
        Tabular.__init__( self, **kwd )
        self.column_names = ['name','taxonomy']

    def sniff( self, filename ):
        """
        Determines whether the file is a SequenceTaxonomy
        """
        try:
            pat = '^([^ \t\n\r\f\v;]+([(]\d+[)])?[;])+$'
            fh = open( filename )
            count = 0
            while True:
                line = fh.readline()
                if not line:
                    break #EOF
                line = line.strip()
                if line:
                    fields = line.split('\t')
                    if len(fields) != 2:
                        return False
                    if not re.match(pat,fields[1]):
                        return False
                    count += 1
                    if count > 10:
                        break
            if count > 0:
                return True
        except:
            pass
        finally:
            fh.close()
        return False

class RDPSequenceTaxonomy(SequenceTaxonomy):
    file_ext = 'rdp.taxonomy'
    """
        A table with 2 columns:
        - SequenceName
        - Taxonomy (semicolon-separated taxonomy in descending order, RDP requires exactly 6 levels deep)
        Example:
          AB001518.1      Bacteria;Bacteroidetes;Sphingobacteria;Sphingobacteriales;unclassified_Sphingobacteriales;
          AB001724.1      Bacteria;Cyanobacteria;Cyanobacteria;Family_II;GpIIa;
          AB001774.1      Bacteria;Chlamydiae;Chlamydiae;Chlamydiales;Chlamydiaceae;Chlamydophila;
    """
    def sniff( self, filename ):
        """
        Determines whether the file is a SequenceTaxonomy
        """
        try:
            pat = '^([^ \t\n\r\f\v;]+([(]\d+[)])?[;]){6}$'
            fh = open( filename )
            count = 0
            while True:
                line = fh.readline()
                if not line:
                    break #EOF
                line = line.strip()
                if line:
                    fields = line.split('\t')
                    if len(fields) != 2:
                        return False
                    if not re.match(pat,fields[1]):
                        return False
                    count += 1
                    if count > 10:
                        break
            if count > 0:
                return True
        except:
            pass
        finally:
            fh.close()
        return False

class ConsensusTaxonomy(Tabular):
    file_ext = 'cons.taxonomy'
    def __init__(self, **kwd):
        """A list of names"""

            fh.close()
        return False

## Qiime Classes

class QiimeMetadataMapping(Tabular):
    MetadataElement( name="column_names", default=[], desc="Column Names", readonly=False, visible=True, no_value=[] )
    file_ext = 'qiimemapping'

    def __init__(self, **kwd):
        """
        http://qiime.sourceforge.net/documentation/file_formats.html#mapping-file-overview
        Information about the samples necessary to perform the data analysis. 

    def set_meta( self, dataset, overwrite = True, skip = None, max_data_lines = None, **kwd ):
        Tabular.set_meta(self, dataset, overwrite, skip, max_data_lines)
        self.set_column_names(dataset)

class QiimeOTU(Tabular):
    """
    Associates OTUs with sequence IDs
    Example:
    0	FLP3FBN01C2MYD	FLP3FBN01B2ALM
    1	FLP3FBN01DF6NE	FLP3FBN01CKW1J	FLP3FBN01CHVM4
    2	FLP3FBN01AXQ2Z
    """
    file_ext = 'qiimeotu'

class QiimeOTUTable(Tabular):
    """
        #Full OTU Counts
        #OTU ID	PC.354	PC.355	PC.356	Consensus Lineage
        0	0	1	0	Root;Bacteria;Firmicutes;"Clostridia";Clostridiales
        1	1	3	1	Root;Bacteria
        2	0	2	2	Root;Bacteria;Bacteroidetes
    """
    MetadataElement( name="column_names", default=[], desc="Column Names", readonly=False, visible=True, no_value=[] )
    file_ext = 'qiimeotutable'
    def init_meta( self, dataset, copy_from=None ):
        tabular.Tabular.init_meta( self, dataset, copy_from=copy_from )
    def set_meta( self, dataset, overwrite = True, skip = None, **kwd ):
        self.set_column_names(dataset) 
    def set_column_names(self, dataset):
        if dataset.has_data():
            dataset_fh = open( dataset.file_name )
            line = dataset_fh.readline()
            line = dataset_fh.readline()
            if line.startswith('#OTU ID'):
                dataset.metadata.column_names = line.strip().split('\t');
            dataset_fh.close()
            dataset.metadata.comment_lines = 2

class QiimeDistanceMatrix(Tabular):
    """
        	PC.354	PC.355	PC.356
        PC.354	0.0	3.177	1.955	
        PC.355	3.177	0.0	3.444
        PC.356	1.955	3.444	0.0
    """
    file_ext = 'qiimedistmat'
    def init_meta( self, dataset, copy_from=None ):
        tabular.Tabular.init_meta( self, dataset, copy_from=copy_from )
    def set_meta( self, dataset, overwrite = True, skip = None, **kwd ):
        self.set_column_names(dataset) 
    def set_column_names(self, dataset):
        if dataset.has_data():
            dataset_fh = open( dataset.file_name )
            line = dataset_fh.readline()
            # first line contains the names
            dataset.metadata.column_names = line.strip().split('\t');
            dataset_fh.close()
            dataset.metadata.comment_lines = 1

class QiimePCA(Tabular):
    """
    Principal Coordinate Analysis Data
    The principal coordinate (PC) axes (columns) for each sample (rows). 
    Pairs of PCs can then be graphed to view the relationships between samples. 
    The bottom of the output file contains the eigenvalues and % variation explained for each PC.
    Example:
    pc vector number	1	2	3
    PC.354	-0.309063936588	0.0398252112257	0.0744672231759
    PC.355	-0.106593922619	0.141125998277	0.0780204374172
    PC.356	-0.219869362955	0.00917241121781	0.0357281314115
    
    
    eigvals	0.480220500471	0.163567082874	0.125594470811
    % variation explained	51.6955484555	17.6079322939
    """
    file_ext = 'qiimepca'

class QiimeParams(Tabular):
    """
###pick_otus_through_otu_table.py parameters###

# OTU picker parameters
pick_otus:otu_picking_method    uclust
pick_otus:clustering_algorithm  furthest

# Representative set picker parameters
pick_rep_set:rep_set_picking_method     first
pick_rep_set:sort_by    otu
    """
    file_ext = 'qiimeparams'

class QiimePrefs(data.Text):
    """
    A text file, containing coloring preferences to be used by make_distance_histograms.py, make_2d_plots.py and make_3d_plots.py.
    Example:
{
'background_color':'black',

'sample_coloring':
        {
                'Treatment':
                {
                        'column':'Treatment',
                        'colors':(('red',(0,100,100)),('blue',(240,100,100)))
                },
                'DOB':
                {
                        'column':'DOB',
                        'colors':(('red',(0,100,100)),('blue',(240,100,100)))
                }
        },
'MONTE_CARLO_GROUP_DISTANCES':
        {
                'Treatment': 10,
                'DOB': 10
        }
}
    """
    file_ext = 'qiimeprefs'

class QiimeTaxaSummary(Tabular):
    """
        Taxon	PC.354	PC.355	PC.356
        Root;Bacteria;Actinobacteria	0.0	0.177	0.955	
        Root;Bacteria;Firmicutes	0.177	0.0	0.444
        Root;Bacteria;Proteobacteria	0.955	0.444	0.0
    """
    MetadataElement( name="column_names", default=[], desc="Column Names", readonly=False, visible=True, no_value=[] )
    file_ext = 'qiimetaxsummary'

    def set_column_names(self, dataset):
        if dataset.has_data():
            dataset_fh = open( dataset.file_name )
            line = dataset_fh.readline()
            if line.startswith('Taxon'):
                dataset.metadata.column_names = line.strip().split('\t');
            dataset_fh.close()

    def set_meta( self, dataset, overwrite = True, skip = None, max_data_lines = None, **kwd ):
        Tabular.set_meta(self, dataset, overwrite, skip, max_data_lines)
        self.set_column_names(dataset)

if __name__ == '__main__':
    import doctest, sys
    doctest.testmod(sys.modules[__name__])