This repository is for the preprint "A generative nonparametric Bayesian model for whole genomes"

Overview

BEAR

Overview

This repository contains code associated with the preprint A generative nonparametric Bayesian model for whole genomes (2021), which proposes Bayesian embedded autoregresive (BEAR) models. The repository provides example BEAR models as well as tools for implementing new models. It enables building, training and evaluating BEAR models on large scale sequencing datasets, including whole genome, transcriptomic and metagenomic data.

Documentation

For instructions on running examples and deploying the BEAR model, consult the documentation at https://bear-model.readthedocs.io/en/latest/.

Authors

This is a project of the Marks Lab in the Systems Biology Department at Harvard Medical School. It was developed by

License

This project is available under the MIT license.

Reference

Preprint: A. N. Amin*, E. N. Weinstein*, D. S. Marks, A generative nonparametric Bayesian model for whole genomes, 2021 (* equal contribution). https://www.biorxiv.org/content/10.1101/2021.05.30.446360v1

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Comments
  • Installation on the cluster

    Installation on the cluster

    Hi,

    I'm trying to install the python package using a Python 3 environment on the cluster. Since I wasn't able to install tensorflow-io-nightly , I changed it to tensorflow-io in the requirements.txt file. When I run pytest to test the installation, there are some errors:

    ERROR bear_model/tests/test_core.py - ValueError: numpy.ndarray size changed, may indicate binary incompati...
    ERROR bear_model/tests/test_dataloader.py - ValueError: numpy.ndarray size changed, may indicate binary inc...
    ERROR bear_model/tests/test_run.py
    ERROR bear_model/tests/test_summarize.py
    

    How can I solve it? Thank you in advance

    opened by FarzanehRah 7
  • Tutorial: Error when running summary.py for the first time without specifying tmp folder

    Tutorial: Error when running summary.py for the first time without specifying tmp folder

    Hi! This error occurs when following the tutorial step by step (after downloading BEAR and installing the required packages).

    Start: Stage 1... 2021-09-11 11:12:47.502770
    Stage 2... 2021-09-11 11:12:49.422647
    Traceback (most recent call last):
      File "summarize.py", line 607, in <module>
        main(args)
      File "summarize.py", line 570, in main
        n_bins = run(args)
      File "summarize.py", line 553, in run
        total_size = stage2(unit2is, args)
      File "summarize.py", line 304, in stage2
        out_size += unit2i.get_size()
      File "summarize.py", line 289, in get_size
        out_size = os.path.getsize(self.out_file)
      File "/home/remita/pyenvs/bear/lib/python3.7/genericpath.py", line 50, in getsize
        return os.stat(filename).st_size
    FileNotFoundError: [Errno 2] No such file or directory: 'data/ysd1_kmc_out_0_full_6.tsv'
    

    After investigation, it appears that KMC cannot find the default tmp folder tests/exdata/tmp/ and throws an error in the stderr data/ysd1_kmc_stderr_0_full_6.txt

    --- kmc ---
    Error: Cannot create file in specified working directory: tests/exdata/tmp/
    --- kmc dump ---
    Error: Cannot open file data/ysd1_kmc_inter_0_full_6.res.kmc_pre
    

    So in the tutorial, it is better to add that the user must create the default tmp folder tests/exdata/tmp/ or specify an existing folder with the option -t of the script summarize.py.

    Thank you.

    opened by maremita 2
  • Python version

    Python version

    I see that this uses Python 3, but it might be nice to specify the specific version that will work - especially for when making conda environments compatible.

    I also noticed this comment in the setup.py:

    NOTE: This file must remain Python 2 compatible for the foreseeable future,

    to ensure that we error out properly for people with outdated setuptools

    and/or pip.

    Not sure if this has any affect on users python version.

    opened by csheare 0
Owner
Debora Marks Lab
Debora Marks Lab
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