Skip to main content

No project description provided

Project 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/v0.37.2.svg
:alt: Commits since latest release
:target: https://github.com/winni2k/abeona/compare/v0.37.2...master


abeona v0.37.2

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>`_.


Changelog
---------

v0.37.2
~~~~~~~

:Date: 2018-10-17

New features
............

* Use kmer mapping (``abeona reads``) to assign reads to subgraphs before quantification of
candidate transcripts with kallisto

Fixes
.....

* Add missing conda dependency ``seqtk`` to ``environment.yml`` for travis CI


Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

abeona-0.37.2.tar.gz (24.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

abeona-0.37.2-py3-none-any.whl (27.1 kB view details)

Uploaded Python 3

File details

Details for the file abeona-0.37.2.tar.gz.

File metadata

  • Download URL: abeona-0.37.2.tar.gz
  • Upload date:
  • Size: 24.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.0.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6

File hashes

Hashes for abeona-0.37.2.tar.gz
Algorithm Hash digest
SHA256 567e48db7da42e51046098cd989d59c8ed597a0381cf94193dad755e994847b5
MD5 889973a10caa1d62b37bc67a1a68b749
BLAKE2b-256 6b1f0d169da827fa83cbdb0eccfcf031affd08d2c3f7e8fdd47f46279ff001f9

See more details on using hashes here.

File details

Details for the file abeona-0.37.2-py3-none-any.whl.

File metadata

  • Download URL: abeona-0.37.2-py3-none-any.whl
  • Upload date:
  • Size: 27.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.0.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6

File hashes

Hashes for abeona-0.37.2-py3-none-any.whl
Algorithm Hash digest
SHA256 8e7dab28e58f65f9e13608efbceb3dbb584bee5102d5a69555447a1b3bb5bbf4
MD5 37b47d74122805d26e6fab28392a3500
BLAKE2b-256 7d3234deeb0a3ad65c251341cde88fe351af742f4eab88678f9174053710c280

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page