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Robustness of Pathway Enrichment Analysis to Transcriptome-Wide Gene Expression Platform

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Practical Applications of Computational Biology & Bioinformatics, 14th International Conference (PACBB 2020) (PACBB 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1240))

Abstract

Progress in technology and increasing knowledge of molecular biology resulted in a variety of transcriptomic expression profiling platforms. Bioinformatics supports this development with various computational techniques like, for example, pathway enrichment analysis. The presented study shows a comprehensive comparison of different transcriptomic platforms and methods of signalling pathway enrichment analysis. All analyses were performed on carefully chosen datasets with control after the most common confounding factors (disease phenotype, experimental design and sample size). It was shown that the most significant differences are observed between enrichment methods themselves rather than transcriptomic profiling platforms. Out of tested methods, CERNO and its combination with SPIA show the highest robustness to the molecular biology technique while ORA enrichment method shows little affection to tested platforms.

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Acknowledgements

This work was co-financed by SUT grant for maintaining and developing research potential (JZ), National Science Centre Poland, grant BITIMS 2015/19/B/ST6/01736 (JP) and European Union grant under the European Social Fund, project no. POWR.03.02.00-00-I029 (KL). All calculations were carried out using GeCONiI infrastructure funded by NCBiR project no. POIG.02.03.01-24-099/13.

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Authors and Affiliations

  1. Department of Data Science and Engineering, The Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Joanna Zyla, Kinga Leszczorz & Joanna Polanska

Authors
  1. Joanna Zyla
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  2. Kinga Leszczorz
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  3. Joanna Polanska
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Corresponding author

Correspondence to Joanna Zyla .

Editor information

Editors and Affiliations

  1. Enhanced Regenerative Medicine, Istituto Italiano di Tecnologia, Genoa, Genova, Italy

    Gabriella Panuccio

  2. Department de Informática, Universidade do Minho, Braga, Portugal

    Miguel Rocha

  3. Computer Science Department, University of Vigo, Vigo, Spain

    Florentino Fdez-Riverola

  4. Institute for Artificial Intelligence and Big Data (AIBIG), Universiti Malaysia Kelantan, Kampus Kota, Kota Bharu, Malaysia

    Mohd Saberi Mohamad

  5. Biotechnology, Intelligent Systems and Educational Technology (BISITE) Research Group, University of Salamanca, Salamanca, Salamanca, Spain

    Roberto Casado-Vara

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Zyla, J., Leszczorz, K., Polanska, J. (2021). Robustness of Pathway Enrichment Analysis to Transcriptome-Wide Gene Expression Platform. In: Panuccio, G., Rocha, M., Fdez-Riverola, F., Mohamad, M., Casado-Vara, R. (eds) Practical Applications of Computational Biology & Bioinformatics, 14th International Conference (PACBB 2020). PACBB 2020. Advances in Intelligent Systems and Computing, vol 1240. Springer, Cham. https://doi.org/10.1007/978-3-030-54568-0_18

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