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High-Throughput Tabular Data Processor - Platform independent graphical tool for processing large data sets.

Piotr Madanecki1, Magdalena Bałut1, Patrick G Buckley2

  • 1Department of Biology and Pharmaceutical Botany, Medical University of Gdansk, Gdansk, Poland.

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|February 13, 2018
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This summary is machine-generated.

High-Throughput Tabular Data Processor (HTDP) is a user-friendly Java tool for analyzing large biological datasets from high-throughput technologies. It simplifies data merging, filtering, and conversion without requiring programming skills.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput technologies generate vast amounts of data requiring specialized bioinformatic analysis.
  • Existing tools often lack flexibility or require programming expertise for data processing.

Purpose of the Study:

  • To present High-Throughput Tabular Data Processor (HTDP), a platform-independent Java program for processing high-throughput experimental data.
  • To provide a user-friendly graphical interface (GUI) for data manipulation, eliminating the need for programming or command-line skills.

Main Methods:

  • HTDP processes any character-delimited column data (e.g., BED, GFF, VCF) from multiple text files.
  • Supports merging, filtering, and data conversion, with options for using external condition files for complex tasks.
  • Designed with a GUI for intuitive, real-time processing of large datasets.

Main Results:

  • Demonstrated flexibility in real-life research, including microarray and next-generation sequencing data analysis.
  • Successfully identified disease-predisposing variants and enabled concurrent analysis of diverse data types.
  • Showcased utility in technical tasks like data merging, reduction, and filtering using external criteria.

Conclusions:

  • HTDP addresses a gap in current GUI software for processing high-throughput tabular data.
  • Its flexible input handling and user-friendly design offer long-term potential in bioinformatics pipelines.
  • Available as open-source software, promoting accessibility and further development.