bioRxivImmunologyPreprint
PALMO: a comprehensive platform for analyzing longitudinal multi-omics data
S. V. Vasaikar, A. K. Savage, Q. Gong, E. Swanson, A. Talla, C. Lord, A. Heubeck, J. Reading, L. T. Graybuck, P. Meijer, T. R. Torgerson, P. Skene, T. Bumol, X.-j. Li
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.
- assay: bulk RNA-seq
- assay: scRNA-seq
- research focus: clustering
- research focus: differential expression
- research focus: trajectory inference
- approach: deep learning
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Muon: multimodal omics analysis framework
Danila Bredikhin, Ilia Kats, Oliver Stegle·Genome biologyPeer-reviewed·Feb 1, 2022
- multiTEMPTED: Joint Dimensionality Reduction of Longitudinal Multi-omic Data with Modality-Specific Temporal Dynamics
Lou Lindsley, Annabel Settle, Pixu Shi·bioRxiv·Sep 6, 2026
- Multi-Omics factor analysis - a framework for unsupervised integration of multi-omic data sets
Ricard Argelaguet, Britta Velten, … Oliver Stegle·Molecular Systems BiologyPeer-reviewed·Jun 1, 2018
- tensorOmics: Data integration for longitudinal omics data using tensor factorisation
Saritha Kodikara, Brendan Lu, … Kim‐Anh Lê Cao·bioRxiv·Feb 12, 2026
- MOSCATO: A Supervised Approach for Analyzing Multi-Omic Single-Cell Data
Lorin M. Towle-Miller, Jeffrey C. Miecznikowski·BMC GenomicsPeer-reviewed·Aug 4, 2022
- Robust Identification of Temporal Biomarkers in Longitudinal Omics Studies
Ahmed A. Metwally, Tom Zhang, … Michael P. Snyder·BioinformaticsPeer-reviewed·Jun 28, 2022