HTSeq--a Python framework to work with high-throughput sequencing data.

Simon Anders,Paul Theodor Pyl,Wolfgang Huber

doi:10.1093/bioinformatics/btu638

Simon Anders, Paul Theodor Pyl + Show 1 more

Open Access

https://doi.org/10.1093/bioinformatics/btu638

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Abstract

Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed.Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes.Availability and implementation: HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq.Contact: sanders@fs.tum.de

Highlights

The rapid technological advance in high-throughput sequencing (HTS) has led to the development of many new kinds of assays, each of which requires the development of a suitable bioinformatical analysis pipeline
A core component of HTSeq is a container class that simplifies working with data associated with genomic coordinates, i.e., values attributed to genomic positions or to genomic intervals
The remainder of the documentation provides references for all classes and functions provided by HTSeq, including those classes not used in the highlighted use cases of the tutorial part, such as the facilities to deal with variant-call format (VCF) files

Summary

INTRODUCTION

The rapid technological advance in high-throughput sequencing (HTS) has led to the development of many new kinds of assays, each of which requires the development of a suitable bioinformatical analysis pipeline. We present HTSeq, a Python library to facilitate the rapid development of scripts for processing and analysis of highthroughput sequencing (HTS) data. HTSeq includes parsers for common file formats for a variety of types of input data and is suitable as a general platform for a diverse range of tasks. A core component of HTSeq is a container class that simplifies working with data associated with genomic coordinates, i.e., values attributed to genomic positions (e.g., read coverage) or to genomic intervals (e.g., genomic features such as exons or genes). The documentation, as well as HTSeq’s design, is geared towards allowing users with only moderate Python knowledge to create their own scripts, while shielding more advanced internals from the user

Parser and record objects

The GenomicArray class

DOCUMENTATION AND CODING STRATEGIES

HTSEQ-COUNT

DISCUSSION