Using ‘collective omics data’ for biomedical research training

Abstract

Summary Systems‐scale molecular profiling data accumulating in public repositories may constitute a useful resource for immunologists. It is for instance likely that information relevant to their chosen line of research be found among the more than 90,000 data series available in the NCBI Gene Expression Omnibus. Such ‘collective omics data’ may also be employed as source material for training purposes. This is the case when training curricula aim at the development of bioinformatics skills necessary for the analysis, interpretation or visualization of data generated on global scales. But ‘collective omics data’ may also be reused for training purposes to foster the development of the skills and ‘mental habits’ underpinning traditional reductionist science approaches. This review describes a small‐scale initiative involving investigators, for the most part immunologists, having engaged in a range of training activities relying on ‘collective omics data’.

Identification of erythroid cell positive blood transcriptome phenotypes associated with severe respiratory syncytial virus infection

“…Finally, organization of the workshop upon which the analyses presented in this article are based provided an opportunity to put to the test a given format for the third training module of the three part “COD” training program currently being developed at Sidra (COD3 = global scale analyses and visualization approaches using public omics data as source of training material – [1]). About only have the time during this weeklong workshop was dedicated to re-analysis of public RSV data and it did not prove sufficient for trainees to complete the analyses during the time imparted.…”

“…The availability of vast collections of transcriptome dataset in GEO, the NCBI Gene Expression Omnibus, prompted the development of a training program relying on this resource. The framework for this program was described in a recent review [1]. Briefly, it consists of three training modules: “COD1” focuses on reductionist investigation approaches and relies on transcript profiles of single gene candidates across multiple datasets.…”

Elevation of FAM129A in neutrophils exposed to serum of patients with severe sepsis: in silico investigations during a hands on training workshop and follow on validation of protein expression in neutrophils

“…Briefly, a workshop was organized in November of 2018 at Sidra Medicine in Doha, Qatar. It consisted in applying reductionist investigation approaches while using public transcriptome data as source of training material (COD1 training module [4]). Trainees who joined the workshop carried out hands on activities focusing on two candidate genes, ANXA3 and FAM129A.…”

“…The GXB tool has been described in details in an earlier publication [5]. Constitution of curated dataset collections is an activity that is undertaken as part of the COD2 training module, as described in a recent review [4].…”

“…This transcriptome dataset which at the time was deposited in the NCBI’s gene expression omnibus was employed more recently in the context of a training workshop conducted at Sidra Medicine in Doha Qatar in November of 2018. Trainees applied reductionist investigation approaches, using available public omics data as a starting point (COD1 training module, as described in: [4]). Individual reports from trainees are included with this submission as supplementary files.…”