Metadata-Version: 1.2
Name: maslongbow
Version: 0.4.5.8
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
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        .. |pypi_v| image:: https://img.shields.io/pypi/v/maslongbow
        .. _pypi_v: https://pypi.org/project/maslongbow/
        .. |pypi_dm| image:: https://img.shields.io/pypi/dm/maslongbow
        .. _pypi_dm: https://pypi.org/project/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
        
        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
        
            # Annotate reads according to the mas15 model
            longbow annotate -m mas15 -o ann.bam mas15_test_input.bam
        
            # Generate annotation stats and automatic QC figures in .png and .svg format
            longbow stats -o stats ann.bam
        
            # Segment reads according to the model annotations
            longbow segment -o seg.bam ann.bam
        
            # Filter out improperly-constructed arrays (will generate filter_passed.bam and filter_failed.bam files)
            longbow filter -o filter seg.bam
        
            # 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
