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Amplicon Sequencing using the Long-Read Sequencing Technologies
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SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses.

Tomáš Vetrovský1, Petr Baldrian1, Daniel Morais1

  • 1Institute of Microbiology of the CAS, 14220 Prague 4, Czech Republic.

Bioinformatics (Oxford, England)
|February 17, 2018
PubMed
Summary
This summary is machine-generated.

Modern molecular methods generate vast microbial sequencing data. SEED 2 offers a user-friendly graphical interface for analyzing amplicon sequencing data, simplifying microbial community analysis for researchers without command-line expertise.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Modern molecular methods and sequencing technologies have greatly advanced microbial community analysis.
  • The analysis of large-scale sequencing data requires significant computational resources and specialized expertise.
  • Existing command-line software for sequence analysis presents steep learning curves and accessibility challenges for many researchers.

Purpose of the Study:

  • To develop a user-friendly graphical interface for handling high-throughput amplicon sequencing data.
  • To provide researchers with accessible tools for microbial community analysis, regardless of their command-line proficiency.
  • To streamline the processing and interpretation of amplicon sequencing data from various platforms.

Main Methods:

  • SEED 2 was developed using Object Pascal, incorporating internal functions and external software for data processing.
  • The software provides a graphical user interface (GUI) for Windows operating systems.
  • It is designed to handle amplicon sequencing data from marker genes obtained via Illumina, IonTorrent, or Sanger sequencing.

Main Results:

  • SEED 2 is a unique sequence visualizer equipped with tools for microbial community marker amplicon data.
  • It enables users to process raw sequencing data, identify taxa, generate OTU tables, create alignments, and construct phylogenetic trees.
  • Standard dual-core laptops with 8 GB RAM can process approximately 8 million Illumina PE 300 bp sequences (around 4 GB of data).

Conclusions:

  • SEED 2 simplifies complex amplicon sequencing data analysis through an intuitive graphical interface.
  • It empowers researchers to effectively analyze microbial community structures without extensive computational training.
  • The freeware software is readily available, self-contained, and requires no installation, promoting wider accessibility.