semvec/pypi-packages huggingface dataset:
treehouse 0.2.0
High-performance tree traversal
Requires Python: >=3.6

.. image:: https://img.shields.io/pypi/v/treehouse.svg
   :target: `PyPI link`_

.. image:: https://img.shields.io/pypi/pyversions/treehouse.svg
   :target: `PyPI link`_

.. _PyPI link: https://pypi.org/project/treehouse

.. image:: https://github.com/jaraco/treehouse/workflows/Automated%20Tests/badge.svg
   :target: https://github.com/jaraco/treehouse/actions?query=workflow%3A%22Automated+Tests%22
   :alt: Automated Tests

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
   :target: https://github.com/psf/black
   :alt: Code style: Black

.. .. image:: https://readthedocs.org/projects/treehouse/badge/?version=latest
..    :target: https://treehouse.readthedocs.io/en/latest/?badge=latest


Traverse Python object trees (dicts/lists) at C speed::

    >>> import treehouse
    >>> treehouse.map_values(int, {"a": "1", "b": {"c": "2"}})
    {"a": 1, "b": {"c": 2}}
goodorfs 1.0
A a tool to find coding orfs
Requires Python: >3.5.2

Introduction
------------

GOODORFS is a tool to classify open reading frames into coding and noncoding

It takes as input a fasta file representing the entire genome.  It then finds all potential open reading frames, and then for each, calculates the Energy Density Profile from the amino acid frequency.

To install `GOODORFS`,
```
git clone https://github.com/deprekate/goodorfs.git
cd goodorfs
python3 setup.py install

```

To run `GOODORFS` simply provide the path to a fasta file.  The default output is the same format as Glimmers LONGORFS program, in order to serve as a drop in replacement.
The columns are: orf_id, start_location, stop_location, frame, a bunch of zeros as filler
```
$ goodorfs.py tests/NC_001416.fna
00001     191     736  +2   0.000
00002     711    2636  +3   0.000
00003    2633    2839  +2   0.000
00004    3270    2830  -1   0.000
00005    2836    4437  +1   0.000
00006    5095    4604  -2   0.000
00007    4283    5737  +2   0.000
...
```

Additionally `GOODORFS` can also output the nucleotide sequences in fasta format for use in other applications:
```
$ good-orfs.py -Y fna tests/NC_001416.fna | head
>NC_001416_orf1 [START=191] [STOP=736]
ATGGAAGTCAACAAAAAGCAGCTGGCTGACATTTTCGGTGCGAGTATCCGTACCATTCA...
>NC_001416_orf2 [START=711] [STOP=2636]
GTGAATATATCGAACAGTCAGGTTAACAGGCTGCGGCATTTTGTCCGCGCCGGGCTTCG...
>NC_001416_orf3 [START=2633] [STOP=2839]
ATGACGCGACAGGAAGAACTTGCCGCTGCCCGTGCGGCACTGCATGACCTGATGACAGG...
>NC_001416_orf4 [START=3270] [STOP=2830]
GTGCATGGCCACACCTTCCCGAATCATCATGGTAAACGTGCGTTTTCGCTCAACGTCAA...
...
```