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A tool to identify full length cDNA reads
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README.md

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Pychopper

CircleCI install with bioconda

A tool to identify full length cDNA reads. Primers have to be specified as they are on the forward strand.

Getting Started

Installation

Install via pip:

pip install git+https://github.com/nanoporetech/pychopper.git

Or clone the repository:

git clone https://github.com/nanoporetech/pychopper.git

And install the package:

python setup.py install

Install the package in developer mode:

python setup.py develop

Run the tests:

make test

Build the documentation:

make docs

Issue make help to get a list of make targets.

Usage

usage: cdna_classifier.py [-h] -b primers [-i input_format] [-g aln_params]
                          [-t target_length] [-s score_percentile]
                          [-n sample_size] [-r report_pdf] [-u unclass_output]
                          [-S stats_output] [-A scores_output] [-x]
                          [-l heu_stringency] [-T nr_cores]
                          input_fastx output_fastx

Tool to identify full length cDNA reads. Primers have to be specified as they
are on the forward strand.

positional arguments:
  input_fastx          Input file.
  output_fastx         Output file.

optional arguments:
  -h, --help           show this help message and exit
  -b primers           Primers fasta.
  -i input_format      Input/output format (fastq).
  -g aln_params        Alignment parameters (match,
                       mismatch,gap_open,gap_extend).
  -t target_length     Number of bases to scan at each end (200).
  -s score_percentile  Score cutoff percentile (98).
  -n sample_size       Number of samples when calculating score cutoff
                       (100000).
  -r report_pdf        Report PDF.
  -u unclass_output    Write unclassified reads to this file.
  -S stats_output      Write statistics to this file.
  -A scores_output     Write alignment scores to this file.
  -x                   Use more sensitive (and error prone) heuristic mode
                       (False).
  -l heu_stringency    Stringency in heuristic mode (0.25).

Example usage:

cdna_classifier.py -b cdna_barcodes.fas -r report.pdf -u unclassified.fq input.fq full_length_output.fq

Example usage in heuristic mode which is more sensitive (and more error prone):

cdna_classifier.py -x -b cdna_barcodes.fas -r report.pdf -u unclassified.fq input.fq full_length_output.fq

The primers have to specified as they are on the forward strand (see data/cdna_barcodes.fas for an example). The score cutoffs for each primer are calculated by aligning them against random sequences and taking the -s percentile of the score distribution (98 by default).

Contributing

  • Please fork the repository and create a merge request to contribute.
  • Use bumpversion to manage package versioning.
  • The code should be PEP8 compliant, which can be tested by make lint.

Help

Licence and Copyright

(c) 2018 Oxford Nanopore Technologies Ltd.

This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

FAQs and tips

References and Supporting Information

See the post announcing the tool at the Oxford Nanopore Technologies community here.

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