Modern biomedical research is increasingly quantitative. The next generation of researchers will need an entirely new set of quantitative skills to fully take advantage of the data they create. In response to this need, the goal of the current R25 proposal is to transform an existing, 5-day bioinformatics techniques course into a new, two-week short course, Reproducible and FAIR Bioinformatics Analysis of Omics Data, to provide a unique educational opportunity for biomedical research scientists-in-training to begin to develop core competencies in bioinformatics and biostatistical analyses of large datasets. The new course will also address NIH priorities including rigor and reproducibility and Findable, Accessible, Interoperable and Reusable (FAIR) data principles. During the last five years, the Dartmouth faculty who are serving as Principal Investigators have taught a 5-day course at the MDI Biological Laboratory on bioinformatics and biostatistics to ~40 trainees/year (202 total). Based on overwhelmingly positive feedback, the current project will extend this 5-day course into a longer, two-week short course at the MDI Biological Laboratory that will feature a low student-to- instructor ratio (5:1), more hands-on experiential learning, and exceptional faculty who are highly experienced in teaching and performing big-data analyses. The new course is designed to accommodate ~35 trainees per year (175 total over the five-year R25 project). It will incorporate modules on biostatistics, scientific rigor and reproducibility, and FAIR data principles. The course design will also involve a short conceptual presentation, followed by an exercise in which students will gain confidence by applying a new skill. Each active-learning session will have three levels of difficulty (beginner, intermediate, and advanced) to allow each student to progress at their own pace. The low student-to-faculty ratio will allow course facilitators to guide participants through realistic challenges without causing frustration.
The specific aims of the proposed course include:
Specific Aim 1. Develop a two-week short course primarily for postdoctoral fellows and graduate students that improves their ability to design and analyze omics experiments such as RNA-seq, 16S (microbiome), metagenomics, and sc-RNA-seq data;
Specific Aim 2. Enhance the impact of research by biomedical scientists by teaching them the Responsible Conduct of Research, the secure and ethical use of data, as well as rigor and reproducibility and FAIR data principles;
Specific Aim 3. Disseminate the training curriculum to a broad audience;
and Specific Aim 4. Evaluate the short- and long-term impacts of the course on students, including a long-term follow-up to determine students? confidence in and actual integration of bioinformatics, biostatistics, and FAIR data principles into their research, and the reported impact of this course on their career trajectory and competitiveness in the job market. In summary, the proposed course will provide a unique cross- training, educational opportunity for biomedical research scientists-in-training to begin to develop core competency in bioinformatics and biostatistical analyses of large data sets.
The goal of our two-week short course, Reproducible and FAIR Bioinformatics Analysis of Omics Data, is to provide a unique cross-training, experiential, educational opportunity for biomedical research scientists-in- training to begin to develop core competency in bioinformatics and biostatistical analyses of large data sets.
