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

Edoardo Morandi1,2, Matteo Cereda2, Danny Incarnato1,2

  • 1Department of Life Sciences and System Biology, University of Turin, Turin, Italy.

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|October 16, 2019
PubMed
Summary
This summary is machine-generated.

HaTSPiL is a new Python tool that simplifies complex next-generation sequencing (NGS) data analysis. It ensures reliable and reproducible results by automatically managing diverse analysis workflows, even with large datasets.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Next-generation sequencing (NGS) generates vast amounts of data for research and health studies.
  • Increasing data volume necessitates improved software and reliable, reproducible analysis workflows.
  • Managing diverse NGS applications and workflows presents a significant challenge to maintaining reliability.

Purpose of the Study:

  • Introduce HaTSPiL, a novel Python-powered command-line interface (CLI) tool.
  • Provide a reliable solution for managing diverse next-generation sequencing data analysis approaches.
  • Enhance the automation and customizability of high-throughput sequencing pipelines.

Main Methods:

  • Developed HaTSPiL as a modular and customizable Python CLI tool.
  • Implemented a filename barcoding system with human-readable conventions for automatic workflow selection.
  • Designed the tool to handle various data analysis workflows and parameters with high reliability.

Main Results:

  • HaTSPiL effectively manages different data analysis approaches for next-generation sequencing.
  • The tool ensures reliability and reproducibility in high-throughput sequencing data analysis.
  • Filename barcoding enables automatic selection of appropriate workflows and parameters.

Conclusions:

  • HaTSPiL offers a flexible and reliable solution for next-generation sequencing data analysis.
  • The software is open-source (MIT license) and available for extension and customization.
  • Facilitates efficient management of complex bioinformatics workflows.