NAME
pychopper - package documentation
COMMAND LINE TOOLS
FULL API REFERENCE
pychopper
pychopper package
Subpackages
pychopper.phmm_data package
Module contents
pychopper.primer_data package
Module contents
pychopper.scripts package
Submodules
pychopper.scripts.pychopper module
- pychopper.scripts.pychopper.main()
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Parse command line arguments.
Module contents
pychopper.tests package
Submodules
pychopper.tests.test_detector module
- class pychopper.tests.test_detector.TestDetector(methodName='runTest')
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Bases: unittest.case.TestCase
Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.
- testPairAlign()
- testScoreCutoff()
pychopper.tests.test_regression_simple module
- class pychopper.tests.test_regression_simple.TestIntegration(methodName='runTest')
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Bases: unittest.case.TestCase
Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.
- testIntegration()
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Integration test.
- testIntegration_umi()
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Integration test.
Module contents
Submodules
pychopper.alignment_hits module
- pychopper.alignment_hits.process_hits(hits, max_score)
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Process alignment hits by removing overlaps
pychopper.chopper module
- pychopper.chopper.analyse_hits(hits, config)
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Segment reads based on alignment hits using dynamic programming. The algorithm is based on the rule that each primer alignment hit can be used only once. Hence if a segment is included, the next one has to be excluded.
- pychopper.chopper.chopper_edlib(reads, primers, config, max_ed, cutoff, pool, min_batch)
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Segment using the edlib/parasail backend
- pychopper.chopper.chopper_phmm(reads, phmm_file, config, cutoff, threads, pool, min_batch)
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Segment using the profile HMM backend
- pychopper.chopper.segments_to_reads(read, segments, keep_primers, bam_tags, detect_umis)
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Convert segments to output reads with annotation
pychopper.common_structures module
- class pychopper.common_structures.Hit(Ref, RefStart, RefEnd, Query, QueryStart, QueryEnd, Score)
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Bases: tuple
Create new instance of Hit(Ref, RefStart, RefEnd, Query, QueryStart, QueryEnd, Score)
- Query
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Alias for field number 3
- QueryEnd
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Alias for field number 5
- QueryStart
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Alias for field number 4
- Ref
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Alias for field number 0
- RefEnd
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Alias for field number 2
- RefStart
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Alias for field number 1
- Score
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Alias for field number 6
- class pychopper.common_structures.Segment(Left, Start, End, Right, Strand, Len)
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Bases: tuple
Create new instance of Segment(Left, Start, End, Right, Strand, Len)
- End
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Alias for field number 2
- Left
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Alias for field number 0
- Len
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Alias for field number 5
- Right
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Alias for field number 3
- Start
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Alias for field number 1
- Strand
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Alias for field number 4
- class pychopper.common_structures.Seq(Id, Name, Seq, Qual, Umi)
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Bases: tuple
Create new instance of Seq(Id, Name, Seq, Qual, Umi)
- Id
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Alias for field number 0
- Name
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Alias for field number 1
- Qual
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Alias for field number 3
- Seq
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Alias for field number 2
- Umi
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Alias for field number 4
pychopper.edlib_backend module
- pychopper.edlib_backend.find_locations(reads, all_primers, max_ed, pool, min_batch)
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Find alignment hits of all primers in all reads using the edlib/parasail backend
- pychopper.edlib_backend.find_umi_single(params)
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Find UMI in a single reads using the edlib/parasail backend
pychopper.hmmer_backend module
- pychopper.hmmer_backend.find_locations(reads, phmm_file, E, pool, min_batch)
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Find alignment hits of all primers in all reads using the pHMM/nhmmscan backend
pychopper.parasail_backend module
- pychopper.parasail_backend.first_cigar(cigar)
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Extract details of the first operation in a cigar string.
- pychopper.parasail_backend.pair_align(reference, query, query_name, subs_mat, params)
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Perform pairwise local alignment using parsail-python
- pychopper.parasail_backend.process_alignment(aln, query, query_name, aln_params)
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Process an alignment, extracting score, start and end.
- pychopper.parasail_backend.refine_locations(read, all_primers, locations, aln_params={'gap_extend': 1, 'gap_open': 1, 'match': 1, 'mismatch': -2}, subs_mat=<parasail.bindings_v2.Matrix object>)
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Refine alignment edges based on local alignment
pychopper.report module
- class pychopper.report.Report(pdf)
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Bases: object
Class for plotting utilities on the top of matplotlib. Plots are saved in the specified file through the PDF backend.
- Parameters
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- •
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self -- object.
- •
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pdf -- Output pdf.
- Returns
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The report object.
- Return type
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Report
- close()
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Close PDF backend. Do not forget to call this at the end of your script or your output will be damaged!
- Parameters
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self -- object
- Returns
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None
- Return type
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object
- plot_arrays(data_map, title='', xlab='', ylab='', marker='.', legend_loc='best', legend=True, vlines=None, vlcolor='green', vlwitdh=0.5)
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Plot multiple pairs of data arrays.
- Parameters
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- •
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self -- object.
- •
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data_map -- A dictionary with labels as keys and tupples of data arrays (x,y) as values.
- •
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title -- Figure title.
- •
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xlab -- X axis label.
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ylab -- Y axis label.
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marker -- Marker passed to the plot function.
- •
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legend_loc -- Location of legend.
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legend -- Plot legend if True
- •
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vlines -- Dictionary with labels and positions of vertical lines to draw.
- •
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vlcolor -- Color of vertical lines drawn.
- •
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vlwidth -- Width of vertical lines drawn.
- Returns
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None
- Return type
-
object
- plot_bars_simple(data_map, title='', xlab='', ylab='', alpha=0.6, xticks_rotation=0, auto_limit=False)
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Plot simple bar chart from input dictionary.
- Parameters
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- •
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self -- object.
- •
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data_map -- A dictionary with labels as keys and data as values.
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title -- Figure title.
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xlab -- X axis label.
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ylab -- Y axis label.
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alpha -- Alpha value.
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xticks_rotation -- Rotation value for x tick labels.
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auto_limit -- Set y axis limits automatically.
- Returns
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None
- Return type
-
object
- plot_histograms(data_map, title='', xlab='', ylab='', bins=50, alpha=0.7, legend_loc='best', legend=True, vlines=None)
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Plot histograms of multiple data arrays.
- Parameters
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- •
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self -- object.
- •
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data_map -- A dictionary with labels as keys and data arrays as values.
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title -- Figure title.
- •
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xlab -- X axis label.
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ylab -- Y axis label.
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bins -- Number of bins.
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alpha -- Transparency value for histograms.
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legend_loc -- Location of legend.
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legend -- Plot legend if True.
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vlines -- Dictionary with labels and positions of vertical lines to draw.
- Returns
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None
- Return type
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object
- save_close()
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Utility method to save and close figure.
pychopper.seq_utils module
- pychopper.seq_utils.base_complement(k)
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Return complement of base.
Performs the subsitutions: A<=>T, C<=>G, X=>X for both upper and lower case. The return value is identical to the argument for all other values.
- Parameters
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k -- A base.
- Returns
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Complement of base.
- Return type
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str
- pychopper.seq_utils.errs_tab(n)
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Generate list of error rates for qualities less than equal than n.
- pychopper.seq_utils.get_primers(primers)
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Load primers from fasta file
- pychopper.seq_utils.get_runid(desc)
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Parse out runid from sequence description.
- pychopper.seq_utils.mean_qual(quals, qround=False, tab=[1.0, 0.7943282347242815, 0.6309573444801932, 0.5011872336272722, 0.3981071705534972, 0.31622776601683794, 0.251188643150958, 0.19952623149688797, 0.15848931924611134, 0.12589254117941673, 0.1, 0.07943282347242814, 0.06309573444801933, 0.05011872336272722, 0.039810717055349734, 0.03162277660168379, 0.025118864315095794, 0.0199526231496888, 0.015848931924611134, 0.012589254117941675, 0.01, 0.007943282347242814, 0.00630957344480193, 0.005011872336272725, 0.003981071705534973, 0.0031622776601683794, 0.0025118864315095794, 0.001995262314968879, 0.001584893192461114, 0.0012589254117941675, 0.001, 0.0007943282347242813, 0.000630957344480193, 0.0005011872336272725, 0.00039810717055349735, 0.00031622776601683794, 0.00025118864315095795, 0.00019952623149688788, 0.00015848931924611142, 0.00012589254117941674, 0.0001, 7.943282347242822e-05, 6.309573444801929e-05, 5.011872336272725e-05, 3.9810717055349695e-05, 3.1622776601683795e-05, 2.5118864315095822e-05, 1.9952623149688786e-05, 1.584893192461114e-05, 1.2589254117941661e-05, 1e-05, 7.943282347242822e-06, 6.30957344480193e-06, 5.011872336272725e-06, 3.981071705534969e-06, 3.162277660168379e-06, 2.5118864315095823e-06, 1.9952623149688787e-06, 1.584893192461114e-06, 1.2589254117941661e-06, 1e-06, 7.943282347242822e-07, 6.30957344480193e-07, 5.011872336272725e-07, 3.981071705534969e-07, 3.162277660168379e-07, 2.5118864315095823e-07, 1.9952623149688787e-07, 1.584893192461114e-07, 1.2589254117941662e-07, 1e-07, 7.943282347242822e-08, 6.30957344480193e-08, 5.011872336272725e-08, 3.981071705534969e-08, 3.162277660168379e-08, 2.511886431509582e-08, 1.9952623149688786e-08, 1.5848931924611143e-08, 1.2589254117941661e-08, 1e-08, 7.943282347242822e-09, 6.309573444801943e-09, 5.011872336272715e-09, 3.981071705534969e-09, 3.1622776601683795e-09, 2.511886431509582e-09, 1.9952623149688828e-09, 1.584893192461111e-09, 1.2589254117941663e-09, 1e-09, 7.943282347242822e-10, 6.309573444801942e-10, 5.011872336272714e-10, 3.9810717055349694e-10, 3.1622776601683795e-10, 2.511886431509582e-10, 1.9952623149688828e-10, 1.584893192461111e-10, 1.2589254117941662e-10, 1e-10, 7.943282347242822e-11, 6.309573444801942e-11, 5.011872336272715e-11, 3.9810717055349695e-11, 3.1622776601683794e-11, 2.5118864315095823e-11, 1.9952623149688828e-11, 1.5848931924611107e-11, 1.2589254117941662e-11, 1e-11, 7.943282347242821e-12, 6.309573444801943e-12, 5.011872336272715e-12, 3.9810717055349695e-12, 3.1622776601683794e-12, 2.5118864315095823e-12, 1.9952623149688827e-12, 1.584893192461111e-12, 1.258925411794166e-12, 1e-12, 7.943282347242822e-13, 6.309573444801942e-13, 5.011872336272715e-13, 3.981071705534969e-13, 3.162277660168379e-13, 2.511886431509582e-13, 1.9952623149688827e-13, 1.584893192461111e-13])
-
Calculate average basecall quality of a read. Receive the ascii quality scores of a read and return the average quality for that read First convert Phred scores to probabilities, calculate average error probability convert average back to Phred scale
- pychopper.seq_utils.random(size=None)
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Return random floats in the half-open interval [0.0, 1.0). Alias for random_sample to ease forward-porting to the new random API.
- pychopper.seq_utils.readfq(fp, sample=None, min_qual=None, rfq_sup={})
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Below function taken from https://github.com/lh3/readfq/blob/master/readfq.py Much faster parsing of large files compared to Biopyhton.
- pychopper.seq_utils.record_size(read, in_format='fastq')
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Calculate record size.
- pychopper.seq_utils.revcomp_seq(seq)
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Reverse complement sequence record
- pychopper.seq_utils.reverse_complement(seq)
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Return reverse complement of a string (base) sequence.
- Parameters
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seq -- Input sequence.
- Returns
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Reverse complement of input sequence.
- Return type
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str
- pychopper.seq_utils.writefq(r, fh)
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Write read to fastq file
pychopper.utils module
- pychopper.utils.batch(iterable, size)
- pychopper.utils.check_command(cmd)
- pychopper.utils.check_min_hmmer_version(major, minor)
- pychopper.utils.count_fastq_records(fname, size=128000000, opener=<built-in function open>)
- pychopper.utils.hit2bed(hit, read)
- pychopper.utils.parse_config_string(s)
Module contents
- •
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Index
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Module Index
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Search Page
AUTHOR
ONT Applications Group
COPYRIGHT
2022, Oxford Nanopore Technologies Ltd.