semvec/pypi-packages huggingface dataset:
tendril-utils-gerber 0.2.0
Gerber file manipulation utilities for Tendril
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*
Keywords: tendril


.. image:: https://img.shields.io/pypi/v/tendril-utils-gerber.svg?logo=pypi
    :target: https://pypi.org/project/tendril-utils-gerber

.. image:: https://img.shields.io/pypi/pyversions/tendril-utils-gerber.svg?logo=pypi
    :target: https://pypi.org/project/tendril-utils-gerber

.. image:: https://img.shields.io/travis/tendril-framework/tendril-utils-gerber.svg?logo=travis
    :target: https://travis-ci.org/tendril-framework/tendril-utils-gerber

.. image:: https://img.shields.io/coveralls/github/tendril-framework/tendril-utils-gerber.svg?logo=coveralls
    :target: https://coveralls.io/github/tendril-framework/tendril-utils-gerber

.. image:: https://img.shields.io/codacy/grade/6ab97bf07ca24a2da5c84e71f366035c?logo=codacy
    :target: https://www.codacy.com/app/chintal/tendril-utils-gerber

.. image:: https://img.shields.io/requires/github/tendril-framework/tendril-utils-gerber.svg
    :target: https://requires.io/github/tendril-framework/tendril-utils-gerber/requirements

.. image:: https://img.shields.io/pypi/l/tendril-utils-gerber.svg
    :target: https://www.gnu.org/licenses/agpl-3.0.en.html



.. inclusion-marker-do-not-remove

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

TODO Some brief introduction


Package Information
-------------------

The latest version of the documentation, including installation, usage, and
API/developer notes can be found at
`ReadTheDocs <https://tendril-utils-gerber.readthedocs.io/en/latest/index.html>`_.

The latest version of the sources can be found at
`GitHub <https://github.com/tendril-framework/tendril-utils-gerber>`_. Please use 
GitHub's features to report bugs, request features, or submit pull/merge requests.

The principle author for ``tendril-utils-gerber`` is Chintalagiri Shashank. The 
author can be contacted if necessary via the information on the
`author's github profile <https://github.com/chintal>`_ . See the AUTHORS file
for a full list of collaborators and/or contributing authors, if any.

``tendril-utils-gerber`` is distributed under the terms of the
`AGPLv3 license <https://www.gnu.org/licenses/agpl-3.0.en.html>`_ .
A copy of the text of the license is included along with the sources.
hlaquant 0.0.2
HLAQuant - Get HLA allele specific expression

# HLAQuant
### Author: Austin Crinklaw

## What is it?
HLAQuant is a pipeline that produces fast and accurate allele specific expression for HLA genes. This is done by quantifying on the peptide binding groove domain using Salmon with personalized sequences.

## Requirements:
- Linux OS
- NCBI Blast+
- Salmon -- please ensure Salmon is on your PATH!
- Python 3+
  - Python packages: Pandas, BioPython

## How to use:

### Installation:
HLAQuant can be downloaded through PyPI using the following pip command.
```shell
pip install hlaquant
```

### Input  
HLAQuant takes two input files currently. 
- File one (-hla) consists of a sample_id and then a list of alleles corresponding to that sample's typing (tab separated)
- File two (-fastq) consists of a sample_id and then a list of FASTQ files corresponding to that sample (paired-end or single-end)
Examples of these inputs can be found under the 'test_data/' directory

### Usage
- A list of parameters and their descriptions can be found with the -h flag
```shell
python -m HLAQuant -h
```

### Output  
The output will match that of Salmons. It consists of a tab separated file containing the transcript ID (in this case, a specific HLA allele), as well as the number of reads. TPMs can be ignored as they will be inaccurate since we are only quantifying over a few sequences.

## How does it work?
- We first take the list of alleles and fetch the corresponding sequences from IMGT
- Next we extract the sequences corresponding to their groove domains from these sequences
- We build an index for quantification using these G-domain sequences
- We then perform quantification using this index

The paper outlining this method in detail can be found [....somewhere when it is published]

## References:
This pipeline would be unable to work without Salmon

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017). Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods.