HaTSPiL: A modular pipeline for high-throughput sequencing data analysis

Next generation sequencing methods are widely adopted for a large amount of scientific purposes, from pure research to health-related studies. The decreasing costs per analysis led to big amounts of generated data and to the subsequent improvement of software for the respective analyses. As a conseq...

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Bibliographic Details
Published in:PloS one 2019-10, Vol.14 (10), p.e0222512-e0222512
Main Authors: Morandi, Edoardo, Cereda, Matteo, Incarnato, Danny, Parlato, Caterina, Basile, Giulia, Anselmi, Francesca, Lauria, Andrea, Simon, Lisa Marie, Laurence Polignano, Isabelle, Arruga, Francesca, Deaglio, Silvia, Tirtei, Elisa, Fagioli, Franca, Oliviero, Salvatore
Format: Article
Language:English
Subjects:
Bioinformatics
Biology
Biology and life sciences
Cancer
Computer and Information Sciences
Computer programs
Cost analysis
Data Analysis
DNA - chemistry
DNA Barcoding, Taxonomic - methods
DNA sequencing
Engineering and Technology
Genomes
Health
Hematology
High-Throughput Nucleotide Sequencing
Humans
Information management
Life sciences
Medical research
Medicine
Mutation
Next-generation sequencing
Pipelines
Programming languages
Reliability analysis
Reproducibility of Results
Research and analysis methods
Sequence Analysis, DNA - statistics & numerical data
Software
Software reliability
Stem cells
Workflow
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Summary:Next generation sequencing methods are widely adopted for a large amount of scientific purposes, from pure research to health-related studies. The decreasing costs per analysis led to big amounts of generated data and to the subsequent improvement of software for the respective analyses. As a consequence, many approaches have been developed to chain different software in order to obtain reliable and reproducible workflows. However, the large range of applications for NGS approaches entails the challenge to manage many different workflows without losing reliability. We here present a high-throughput sequencing pipeline (HaTSPiL), a Python-powered CLI tool designed to handle different approaches for data analysis with a high level of reliability. The software relies on the barcoding of filenames using a human readable naming convention that contains any information regarding the sample needed by the software to automatically choose different workflows and parameters. HaTSPiL is highly modular and customisable, allowing the users to extend its features for any specific need. HaTSPiL is licensed as Free Software under the MIT license and it is available at https://github.com/dodomorandi/hatspil.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0222512