A comprehensive platform for analyzing longitudinal multi-omics data

Suhas V. Vasaikar (), Adam K. Savage, Qiuyu Gong, Elliott Swanson, Aarthi Talla, Cara Lord, Alexander T. Heubeck, Julian Reading, Lucas T. Graybuck, Paul Meijer, Troy R. Torgerson, Peter J. Skene, Thomas F. Bumol and Xiao-jun Li ()
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Suhas V. Vasaikar: Allen Institute for Immunology
Adam K. Savage: Allen Institute for Immunology
Qiuyu Gong: Allen Institute for Immunology
Elliott Swanson: Allen Institute for Immunology
Aarthi Talla: Allen Institute for Immunology
Cara Lord: Allen Institute for Immunology
Alexander T. Heubeck: Allen Institute for Immunology
Julian Reading: Allen Institute for Immunology
Lucas T. Graybuck: Allen Institute for Immunology
Paul Meijer: Allen Institute for Immunology
Troy R. Torgerson: Allen Institute for Immunology
Peter J. Skene: Allen Institute for Immunology
Thomas F. Bumol: Allen Institute for Immunology
Xiao-jun Li: Allen Institute for Immunology

Nature Communications, 2023, vol. 14, issue 1, 1-16

Abstract: Abstract Longitudinal bulk and single-cell omics data is increasingly generated for biological and clinical research but is challenging to analyze due to its many intrinsic types of variations. We present PALMO ( https://github.com/aifimmunology/PALMO ), a platform that contains five analytical modules to examine longitudinal bulk and single-cell multi-omics data from multiple perspectives, including decomposition of sources of variations within the data, collection of stable or variable features across timepoints and participants, identification of up- or down-regulated markers across timepoints of individual participants, and investigation on samples of same participants for possible outlier events. We have tested PALMO performance on a complex longitudinal multi-omics dataset of five data modalities on the same samples and six external datasets of diverse background. Both PALMO and our longitudinal multi-omics dataset can be valuable resources to the scientific community.

Date: 2023
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DOI: 10.1038/s41467-023-37432-w

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