Metadata-Version: 2.4
Name: presto
Version: 0.7.5
Summary: A bioinformatics toolkit for processing high-throughput lymphocyte receptor sequencing data.
Home-page: http://presto.readthedocs.io
Download-URL: https://github.com/immcantation/presto/tags
Author: Jason Anthony Vander Heiden
Author-email: immcantation@googlegroups.com
License: GNU Affero General Public License 3 (AGPL-3)
Keywords: bioinformatics,sequencing,immunology,adaptive immunity,immunoglobulin,AIRR-seq,Rep-Seq,B cell repertoire analysis,adaptive immune receptor repertoires
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
License-File: LICENSE
Requires-Dist: numpy>=1.8
Requires-Dist: scipy>=0.14
Requires-Dist: pandas>=0.24
Requires-Dist: biopython>=1.81
Requires-Dist: packaging>=23.2
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.. image:: https://img.shields.io/pypi/dm/presto
    :target: https://pypi.org/project/presto
.. image:: https://img.shields.io/static/v1?label=AIRR-C%20sw-tools%20v1&message=compliant&color=008AFF&labelColor=000000&style=plastic
    :target: https://docs.airr-community.org/en/stable/swtools/airr_swtools_standard.html
	
pRESTO - The REpertoire Sequencing TOolkit
================================================================================

pRESTO is a toolkit for processing raw reads from high-throughput sequencing of
B cell and T cell repertoires.

Dramatic improvements in high-throughput sequencing technologies now enable
large-scale characterization of lymphocyte repertoires, defined as the
collection of trans-membrane antigen-receptor proteins located on the surface of
B cells and T cells. The REpertoire Sequencing TOolkit (pRESTO) is composed of a
suite of utilities to handle all stages of sequence processing prior to germline
segment assignment. pRESTO is designed to handle either single reads or
paired-end reads. It includes features for quality control, primer masking,
annotation of reads with sequence embedded barcodes, generation of
unique molecular identifier (UMI) consensus sequences, assembly of paired-end 
reads and identification of duplicate sequences. Numerous options for sequence 
sorting, sampling and conversion operations are also included.
