Metadata-Version: 1.2
Name: abeona
Version: 0.31.2
Summary: UNKNOWN
Home-page: https://github.com/winni2k/abeona
Author: Warren W. Kretzschmar
Author-email: warrenk@kth.se
Maintainer: Warren W. Kretzschmar
Maintainer-email: warrenk@kth.se
License: Apache-2.0
Description: abeona
        ======
        
        .. start-badges
        
        .. list-table::
            :stub-columns: 1
        
            * - tests
              - | |travis|
            * - package
              - | |commits-since|
        
        .. |travis| image:: https://travis-ci.org/winni2k/abeona.svg?branch=master
            :alt: Travis-CI Build Status
            :target: https://travis-ci.org/winni2k/abeona
        
        .. |commits-since| image:: https://img.shields.io/github/commits-since/winni2k/abeona/v0.31.2.svg
            :alt: Commits since latest release
            :target: https://github.com/winni2k/abeona/compare/v0.31.2...master
        
        
        abeona v0.31.2
        
        A simple transcriptome assembler based on kallisto and Cortex graphs.
        
        Installation
        ------------
        
        The easiest way to install abeona is into a `conda <https://conda.io/miniconda.html>`_ environment.
        
        After activating the conda environment, run:
        
        .. code-block:: bash
        
            conda install abeona -c conda-forge -c bioconda
        
        Running
        -------
        
        The principal command is `abeona assemble`. This command assembles transcripts from cleaned
        short-read RNA-seq reads in FASTA or FASTQ format. For more information, see:
        
        .. code-block:: bash
        
            abeona assemble --help
        
        Toy Example
        ~~~~~~~~~~~
        
        .. code-block:: bash
        
            # Let's create a FASTA consisting of sub-reads from two transcripts: AAAAACCC and AAAAAGGG
            $ for s in AAAAACC AAAAAGG AAAACCC AAAAGGG; do for i in $(seq 1 3); do echo -e ">_\n$s" >> input.fa; done; done
        
            # Now feed the fasta to the graph assembly step with --fastx-single and to the kallisto filtering
            # step with --kallisto-fastx-single.
            $ abeona assemble -k 5 -m 4 --fastx-single input.fa --kallisto-fastx-single input.fa --kallisto-fragment-length 7 --kallisto-sd 1 -o test
            N E X T F L O W  ~  version 0.31.1
            Launching `assemble.nf` [determined_allen] - revision: 11c20ed355
            [bootstrap_samples:100, fastx_forward:null, fastx_reverse:null, fastx_single:/Users/winni/tmp/input.fa, initial_contigs:null, jobs:2, kallisto_fastx_forward:null, kallisto_fastx_reverse:null, kallisto_fastx_single:/Users/winni/tmp/input.fa, kallisto_fragment_length:7.0, kallisto_sd:1.0, kmer_size:5, max_paths_per_subgraph:0, memory:4, merge_candidates_before_kallisto:false, min_tip_length:0, min_unitig_coverage:4, out_dir:test, quiet:false, resume:false, mccortex:mccortex 5, mccortex_args:--sort --force -m 4G]
            [warm up] executor > local
            [26/119d41] Submitted process > fullCortexGraph
            [fc/585605] Submitted process > cleanCortexGraph
            [dd/40b5fc] Submitted process > pruneCortexGraphOfTips
            [36/f63343] Submitted process > traverseCortexSubgraphs
            [23/6d9033] Submitted process > candidateTranscripts (1)
            [d5/05d417] Submitted process > buildKallistoIndices (1)
            [ac/e36d53] Submitted process > kallistoQuant (1)
            [ec/2b258d] Submitted process > filter_transcripts (1)
            [49/d4c7e3] Submitted process > concatTranscripts
        
            # View the resulting assembled transcripts
            $ zcat test/all_transcripts/transcripts.fa.gz
            >g0_p0 prop_bs_est_counts_ge_1=0.98
            AAAAAGGG
            >g0_p1 prop_bs_est_counts_ge_1=1.0
            AAAAACCC
        
        License
        -------
        
        abeona is distributed under the terms of the
        `Apache License, Version 2.0 <https://choosealicense.com/licenses/apache-2.0>`_.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
