Researchers in Software Development and genomics rely on genetic sequencing and its post-processing analysis for both clinical and research purposes. This sequencing analysis can help researchers identify genetic variants within a population, and collecting this data enables them to align recurring variants
with other factors on a patient’s health record to diagnose genetic illnesses that might have otherwise been overlooked, which is essential in determining therapeutic treatment. The eventual goal of genomic research that expands the ability to study and interpret biological data with this level of precision is the development and democratization of personalized medicine—using an individual’s genomic data to deliver targeted therapies that meet their specific needs.
In order to succeed, genomics research requires not only talent, but close collaboration between a number of specialists, including data scientists, bioinformaticians, informatics analysts, computer scientists, information technologists, and software developers. This last talent pool plays an important, but frequently overlooked, role in making genomic research possible and successful.
Software Development and Genomics
Computer scientists, information technologists, and software developers are all involved in the design and implementation of a number of solutions that ensure that genomic research can move forward. They build tools to facilitate and improve analysis workflow efficiency and pipeline; develop APIs and web interfaces that are used to interpret omics datasets; help to standardize genomic and phenotype data, as well as associated metadata; and integrate omics data with phylogenetics and network biology. Software development skills are also coming into play today as many genomic centers around the world take the step of migrating their research and clinical sequence analysis processes from on-premise servers into the cloud.
Although software is a crucial component of the infrastructure of genomic research, its development poses many challenges. The software must meet the specific needs of the research teams who use it, which requires that it be highly tailored and customized to their workflow, pipeline, and research challenges. Academic researchers, even those who are not trained technologists, frequently have sufficient software development abilities to design and build their own solutions; over the years, this has led to the ad hoc development of genomic software that meets the needs of the moment— “artisanal” homegrown scripts and software packages that owe their effectiveness to the fact that they are borne out of the close pairing of research science and software development.
However, the abundance of these homegrown solutions has, in many cases, resulted in a system that, while comfortable for the researchers who built and inhabit it, is also messy, unstable, and fragile. As technology evolves, these systems need to be re-architected to ensure their survival, and this undertaking requires the expertise of professional technologists. However, off-the-shelf solutions are not necessarily the answer: the software still needs to respond to the particular requirements of the laboratory in which it is used. For this reason—and, fortunately, this is happening—research institutions need to be prepared either to hire
professional programmers in-house, or to work in close collaboration with extramural technology experts able to learn the language of their laboratories.
The best way to demonstrate this need for close collaboration between research scientists and technologists in genomics is through examples of the kinds of work technologists do in this setting. One way that technologists facilitate genomics research is by architecting and building Laboratory Information Management Systems (LIMS). The LIMS plays a crucial role in enabling genomics pipeline analysis, supporting all the high-throughput DNA sequencing work in a genomics laboratory.
It allows for a single person’s DNA sample to be tracked through a variety of processes, from sequencing to digital data conversion to analysis. In order to be effective, the LIMS has to align with laboratory teams’ needs and workflow, which is why close collaboration between the software developers and researchers is key to creating an effective solution. It is also vital that the LIMS be well-built and kept up to date, since there is no room for error in a system that regulates this quantity of complex information. This is why LIMS require expert developers capable of designing a system that runs smoothly and is built to last.
Today, many genomic centers are migrating their research and clinical sequence analysis processes from on-premise servers into the cloud. Ultimately, the benefit of this move is that it will enhance researchers’ ability to participate in data sharing and collaboration, both of which are key to making progress in the field. This is a challenging information-technology management project in that it requires a deep understanding of the various interdependencies between all the people and systems involved in making genomics research possible, not just within a given laboratory, but within the institution that supports it.
The task is made even more challenging by the fact that in many genomic research centers, as stated above, the processes in place are supported by a system comprised of a tangled web of homegrown scripts and software packages. Professional technologists, working in close collaboration with researchers, can assess what is currently in place and work interdepartmentally to determine the best way to recreate these processes in a cloud environment, either by “lifting and shifting” or by re-architecting the processes in a cloud-native manner.
Research in genomics promises to transform the future of medicine, allowing for the diagnosis of genetic diseases and the creation of personalized therapies. In order to succeed, this research requires the support of equally personalized technological solutions to underpin the infrastructure of genomics laboratories. Professional technologists need to work in close collaboration with genomics researchers in order to build long-term, subtle, and powerful solutions that are both responsive and durable.