biostudies-literatureHarris CSNINR NIH HHSNational Cancer InstituteNCI NIH HHS596-607https://www.ebi.ac.uk/biostudies/studies/S-EPMC8726420biostudies-literatureUnknown23(4)The incorporation of omics approaches into symptom science research can provide researchers with information about the molecular mechanisms that underlie symptoms. Most of the omics analyses in symptom science have used a single omics approach. Therefore, these analyses are limited by the information contained within a specific omics domain (e.g., genomics and inherited variations, transcriptomics and gene function). A multi-staged data-integrated multi-omics (MS-DIMO) analysis integrates multiple types of omics data in a single study. With this integration, a MS-DIMO analysis can provide a more comprehensive picture of the complex biological mechanisms that underlie symptoms. The results of a MS-DIMO analysis can be used to refine mechanistic hypotheses and/or discover therapeutic targetsBiological research for nursingMulti-Staged Data-Integrated Multi-Omics Analysis for Symptom Science Research.PMC8726420CA107091R37 CA233774T32 NR016920R01 CA107091R01 CA118658Harris CSCataldo JMiaskowski CAKober KMDhruva AAfalseMulti-Staged Data-Integrated Multi-Omics Analysis for Symptom Science Research.The incorporation of omics approaches into symptom science research can provide researchers with information about the molecular mechanisms that underlie symptoms. Most of the omics analyses in symptom science have used a single omics approach. Therefore, these analyses are limited by the information contained within a specific omics domain (e.g., genomics and inherited variations, transcriptomics and gene function). A multi-staged data-integrated multi-omics (MS-DIMO) analysis integrates multiple types of omics data in a single study. With this integration, a MS-DIMO analysis can provide a more comprehensive picture of the complex biological mechanisms that underlie symptoms. The results of a MS-DIMO analysis can be used to refine mechanistic hypotheses and/or discover therapeutic targets2021-01-01T00:00:00Z2021 Oct2025-04-04T12:04:47.319Z2025-04-04T12:04:47.319ZS-EPMC87264203382727010.1177/10998004211003980