The following testimonials have been freely provided by researchers working in Terra or its earlier incarnation, FireCloud, who share their perspective on how specific features of the platform enabled their work.
Alisa Manning, PhD
Clinical and Translational Epidemiology Unit, Mongan Institute
Massachusetts General Hospital
I have been involved in efforts to link rare non-coding variants to complex diseases since 2011. In the early days, we performed our analysis with whole genome sequence data on our local cluster. The Precision Medicine Initiative made large-scale WGS in epidemiological cohorts available and it became clear that retrieving, storing and analyzing these massive data files would be problematic. Another challenge was the collaborative model that our funding agencies were encouraging — we have collaborators at many other institutions with whom we wanted to share resources, code and analysis results.
We found that FireCloud provided an optimized solution to our challenges. We had to learn a new iterative style of workflow development (involving Cromwell, WDL and docker in addition to FireCloud itself), but as soon as we had our development cycle in place, we were able to develop and deploy our analysis workflows with the engagement and assistance from our collaborators. The platform provides a model for our work to be open-source, with excellent tools to manage user access and cloud computing costs. The development team has been extremely responsive to the needs of the research community with a series of enhancements that have enabled us to perform more sophisticated analyses. I'm excited to start taking advantage of the further improvements in Terra.
Matthieu J. Miossec, PhD
Centre for bioinformatics and integrative biology
Universidad Andrés Bello
I was first introduced to FireCloud in 2018 when my workshop proposal for a conference was merged with one from the Broad Institute’s GATK team. For the purposes of the workshop, we reproduced one of the studies I worked on as a doctoral student and research associate (see Page et al, 2018), which was an opportunity for me to discover the platform in detail. The cloud-computing aspect of FireCloud, in itself tremendously useful, particularly for laboratories that don’t always have direct access to high-performance computer clusters, is only the tip of the iceberg.
FireCloud’s method repository was tremendously helpful in building up the pipeline in a brief amount of time. The repository contains both well-documented featured methods created by the GATK team and public methods contributed by other FireCloud users. In both these repositories we found methods that corresponded closely to what my previous team had implemented on local machines and we were therefore able to clone these instead of starting over from scratch. Crucially, once cloned we could make all the small tweaks necessary for the methods to fit our specifications. This mass sharing of both methods and entire workspaces is surely the future of bioinformatics at a time when reproducibility is strongly needed. I will certainly continue working with FireCloud and Terra going forward.
See the project description and check out the Terra workspace here: