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PALMO: a comprehensive platform for analyzing longitudinal multi-omics data

Vasaikar, S. V.; Savage, A. K.; Gong, Q.; Swanson, E.; Talla, A.; Lord, C.; Heubeck, A.; Reading, J.; Graybuck, L. T.; Meijer, P.; Torgerson, T. R.; Skene, P.; Bumol, T.; Li, X.-j.

2022-10-21 immunology
10.1101/2022.10.17.512585 bioRxiv
Show 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 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.

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