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COVID-19 Biomarkers Detection Using ‘KnowSeq’ R Package

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Bioengineering and Biomedical Signal and Image Processing (BIOMESIP 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12940))

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Abstract

‘KnowSeq’ R Package includes all the essential tools to carry out transcriptomic analysis, providing intuitive functions to build efficient and robust pipelines. In this paper, its capacities are demonstrated in a practical COVID-19 biomarkers detection problem using RNA-Sequencing data. Through Machine Learning techniques such as feature selection and supervised classification models, a clinical decision system for COVID-19 was developed using four genes proposed as COVID-19 signature: OAS3, CXCL9, IFITM1 and IFIT3. These four genes are highly related to different processes that affect the immune system behaviour and its response when facing viruses such as SARS-CoV-2. The final model reaches an accuracy over 97% when predicting over unseen samples.

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Acknowledgements

This work was funded by the Government of Andalusia under the Project CV20-64934 titled “Development of an intelligent platform that allows the integration of heterogeneous information sources (imaging, genetics and proteomics) for the characterization and prediction of virulence and pathogenicity in patients with COVID-19”.

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Authors and Affiliations

  1. Department of Computer Architecture and Technology, University of Granada C.I.T.I.C., Periodista Rafael Gomez Montero, 2, 18014, Granada, Spain

    Javier Bajo-Morales, Daniel Castillo-Secilla, Luis Javier Herrera & Ignacio Rojas

Authors
  1. Javier Bajo-Morales
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  2. Daniel Castillo-Secilla
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  3. Luis Javier Herrera
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  4. Ignacio Rojas
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Corresponding author

Correspondence to Javier Bajo-Morales .

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Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Granada, Granada, Spain

    Daniel Castillo-Secilla

  3. University of Granada, Granada, Spain

    Luis Javier Herrera

  4. Universidad de Granada, Granada, Granada, Spain

    Héctor Pomares

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Open source code is available at https://github.com/jbajo09/BIOMESIP-COVID19-KNOWSEQ for researchers to replicate the KnowSeq pipeline proposed.

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Bajo-Morales, J., Castillo-Secilla, D., Herrera, L.J., Rojas, I. (2021). COVID-19 Biomarkers Detection Using ‘KnowSeq’ R Package. In: Rojas, I., Castillo-Secilla, D., Herrera, L.J., Pomares, H. (eds) Bioengineering and Biomedical Signal and Image Processing. BIOMESIP 2021. Lecture Notes in Computer Science(), vol 12940. Springer, Cham. https://doi.org/10.1007/978-3-030-88163-4_37

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  • DOI: https://doi.org/10.1007/978-3-030-88163-4_37

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