Metadata-Version: 1.2
Name: maslongbow
Version: 0.5.13
Summary: Annotation and segmentation of MAS-seq data
Home-page: https://broadinstitute.github.io/longbow/
Author: Kiran V Garimella, Jonn Smith
Author-email: kiran@broadinstitute.org, jonn@broadinstitute.org
License: BSD 3-Clause
Description: Longbow
        """""""
        
        |GitHub release| |Generic badge| |PyPI version maslongbow|
        
        .. |GitHub release| image:: https://img.shields.io/github/release/broadinstitute/longbow.svg
           :target: https://github.com/broadinstitute/longbow/releases/
        
        .. |Generic badge| image:: https://img.shields.io/badge/Docker-v0.5.13-blue.svg
           :target: https://console.cloud.google.com/gcr/images/broad-dsp-lrma/US/lr-longbow
        
        .. |PyPI version maslongbow| image:: https://img.shields.io/pypi/v/maslongbow.svg
           :target: https://pypi.python.org/pypi/maslongbow/
        
        Longbow is a command line tool to process MAS-ISO-seq data. Longbow employs a generative modelling approach to accurately annotate and segment MAS-ISO-seq's concatenated full-length transcript isoforms from single-cell or bulk long read RNA sequencing libraries.
        
        Documentation for all ``longbow`` commands can be found on the `Longbow documentation page <https://broadinstitute.github.io/longbow/>`_.
        
        Installation
        ------------
        
        ``pip`` is recommended for Longbow installation.
        
        ::
        
           pip install maslongbow
        
        For a pre-built version including all dependencies, access our Docker image.
        
        ::
        
           docker pull us.gcr.io/broad-dsp-lrma/lr-longbow:0.5.13
        
        To install from Github source for development, the following commands can be run.
        
        ::
        
           git clone https://github.com/broadinstitute/longbow.git
           pip install -e longbow/
        
        Getting Started
        ---------------
        
        The commands below illustrate the Longbow workflow on a small library of SIRVs (Spike-in RNA Variant Control Mixes). MAS-ISO-seq concatenated transcripts are annotated, segmented, and filtered using the `mas15` model.  A number of statistics and QC images are generated along the way.  Final filtered transcripts can then be aligned using standard splice-aware long read mappers (e.g. minimap2). More detail for each command can be found in the `full documentation <https://broadinstitute.github.io/longbow/commands.html>`_.
        
        ::
        
            # Download a tiny test dataset (less than 300K)
            wget https://github.com/broadinstitute/longbow/raw/main/tests/test_data/mas15_test_input.bam
            wget https://github.com/broadinstitute/longbow/raw/main/tests/test_data/mas15_test_input.bam.pbi
            wget https://github.com/broadinstitute/longbow/raw/main/tests/test_data/resources/SIRV_Library.fasta
        
            # Basic processing workflow
            longbow annotate -m mas15v2 mas15_test_input.bam | \  # Annotate reads according to the mas15v2 model
              tee ann.bam | \                                     # Save annotated BAM for later
              longbow filter | \                                  # Filter out improperly-constructed arrays
              longbow segment | \                                 # Segment reads according to the model
              longbow extract -o filter_passed.bam                # Extract adapter-free cDNA sequences
        
            # Align reads with long read aligner (e.g. minimap2, pbmm2)
            samtools fastq filter_passed.bam | \
                minimap2 -ayYL --MD -x splice:hq SIRV_Library.fasta - | \
                samtools sort > align.bam &&
                samtools index align.bam
        
        
        Getting help
        ------------
        
        The `Longbow documentation page <https://broadinstitute.github.io/longbow/>`_ provides detailed descriptions of command line options and algorithmic details. If you encounter bugs or have questions/comments/concerns, please file an issue on our `Github page <https://github.com/broadinstitute/longbow/issues>`_.
        
        Developers' guide
        -----------------
        
        For information on contributing to Longbow development, visit our `developer documentation <DEVELOP.md>`_.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >=3.6, <=3.7.9
