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MASHt: Software for statistical analysis of transcriptomes' qualitative features in factorial experiments.

Maria Nuc1, Michal Stanoch1, Hanna Cwiek-Kupczynska1,2

  • 1Institute of Plant Genetics, Polish Academy of Sciences, Strzeszynska 34, 60-479 Poznan, Poland.

Bioinformation
|December 30, 2025
PubMed
Summary

The MASHt toolkit analyzes qualitative transcriptome differences in multifactorial experiments using Mash distances and statistical analyses. This approach enhances sequencing data interpretation beyond gene expression levels.

Keywords:
Transcriptomicsfactorial experimentssequence variationsoftware tools

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Next-Generation Sequencing (NGS) data analysis often focuses on gene expression levels.
  • Qualitative differences between transcriptomes are frequently overlooked in multifactorial experiments.

Purpose of the Study:

  • To introduce the MASHt toolkit for analyzing qualitative variation in sequencing data.
  • To provide a method for exploring transcriptome differences beyond quantitative expression levels.

Main Methods:

  • Computing pairwise Mash distances between sequencing datasets.
  • Performing principal coordinate analysis on the distance matrix.
  • Applying univariate and multivariate analyses of variance to principal coordinates.
  • Supporting analysis on data subsets annotated by specific ontologies.

Main Results:

  • Demonstrated MASHt's utility in analyzing multifactorial sequencing data.
  • Successfully applied MASHt to study the impact of temperature on barley transcriptomes across different genotypes.

Conclusions:

  • MASHt offers a novel approach to assess qualitative transcriptome variation.
  • The toolkit facilitates deeper insights into biological responses in complex experimental designs.