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

• Published in: Bioinformatics (Oxford, England) Vol. 31; no. 2; pp. 166 - 169
• Main Authors: Anders, Simon, Pyl, Paul Theodor, Huber, Wolfgang
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 15.01.2015
• Subjects: Gene Expression Regulation; Genome, Human; Genomics - methods; High-Throughput Nucleotide Sequencing - methods; Humans; Original Papers; Software

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 sc...