HER-Omics, a Model of Transcriptomics Data Integration in EHRs

Technological and computational advancements used to generate and process large sets of biological data (omics data) are driving a critical change in the study of biomedical sciences and medicine. While genomics, transcriptomics, and proteomics, coupled with bioinformatics and biostatistics, are gaining momentum, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. The need for this type of data in a clinical setup is becoming more evident. Hence, integrating omics data in electronic health records (EHRs) is a basis for advancing toward personalized diagnosis and treatments. However, due to the heavy and complex nature of omics data, it is still an ongoing challenge to attempt to integrate them into EHRs in an easily interpretable manner. To this end, we present HER-Omics (HERO), a tool that combines both the patients’ EHR and their Omics data. HERO is lightweight, simple to use, and can be integrated with an existing EHR database. The workflow involves taking raw FASTQ files as input, performing the analysis, and giving a clear and readable output that will aid in the decision-making process. We illustrate the use of this tool by using demi transcriptomics data. This shows a proof of concept that we hope will be developed in a more advanced manner in the near future.