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IGUANER - DIfferential Gene Expression and fUnctionAl aNalyzER

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Big Data Analytics in Astronomy, Science, and Engineering (BDA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14516))

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Abstract

In the past fifteen years, the advent of Next-Generation Sequencing technologies, characterized by high efficiency and reduced costs, has marked a pivotal turn for research across various fields including molecular biology, genetics, and molecular medicine. Projects that would have previously required extensive timeframes and significant investments can now be completed swiftly at a fraction of the cost. A direct consequence of the proliferation of these systems is the exponential increase in data generated by RNA-Seq experiments. Much of this data originates from biological samples (cells, tissues, mucus, etc.) of organisms with either absent or incomplete genomic annotations. Compounding this issue is the fact that the surge in data has not been matched by the development of adequate software tools capable of analyzing RNA-Seq data for such organisms. Currently available tools have several limitations: a) they operate in silos, so they only support certain types of analyses, thus complicating the biological interpretation of results; b) they are often executable only via Web interfaces, overlooking the parallelism and efficiency offered by modern supercomputers; c) functional analysis tools rely on outdated functional annotations or support only a limited set of organisms with genomic annotation; d) only one comparison (between two different experimental conditions) can be tested at each run. In order to overcome these limitations, we present IGUANER - (DIfferential Gene expression and fUnctionAl aNalyzER), a software aimed at ensuring the capability for integrated and up-to-date analysis of RNA-Seq data from any organism, regardless of the level of genomic annotation.

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Notes

  1. 1.

    https://www.mongodb.com/.

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Acknowledgments

Part of this research is based on the Cooperative Research Project at the Research Center for Biomedical Engineering CRP-BE-2057.

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Authors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Valentina Pinna, Franco Liberati & Paolo Bottoni

  2. University of Tuscia, Viterbo, Italy

    Jessica Di Martino, Franco Liberati & Tiziana Castrignanò

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  1. Valentina Pinna
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  2. Jessica Di Martino
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  3. Franco Liberati
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  4. Paolo Bottoni
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  5. Tiziana Castrignanò
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Correspondence to Paolo Bottoni .

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Editors and Affiliations

  1. National Institute of Technology Delhi, New Delhi, Delhi, India

    Shelly Sachdeva

  2. University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yutaka Watanobe

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Pinna, V., Di Martino, J., Liberati, F., Bottoni, P., Castrignanò, T. (2024). IGUANER - DIfferential Gene Expression and fUnctionAl aNalyzER. In: Sachdeva, S., Watanobe, Y. (eds) Big Data Analytics in Astronomy, Science, and Engineering. BDA 2023. Lecture Notes in Computer Science, vol 14516. Springer, Cham. https://doi.org/10.1007/978-3-031-58502-9_5

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  • DOI: https://doi.org/10.1007/978-3-031-58502-9_5

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