Informatics
implement to manage sample and experiment data and workflows.
The adaptable, extensible systems required by next-generation genomics labs are hard to buy and even harder to build. Many commercial LIMS designed for NGS research can be rigid and pre- scriptive about how work proceeds – and changes to the out-of-the-box configuration are discour- aged and often impossible. Labs also have the option to work with broad enterprise LIMS ven- dors, who will build tailored systems, but at a cost – these systems take time and money to devel- op and when a lab needs change (and in next-gen- eration sequencing, change is guaranteed), the ven- dor will need to update the system.
Given that commercial software vendors have trouble building flexible, adaptable LIMS, it is sur- prising how many labs opt to build their own LIMS. The promise of implementing exactly the system they want is appealing, but these labs ulti- mately discover that maintaining and updating software over time drains critical resources. Does a leading-edge NGS lab also want to become an expert in software design and development? The best answer to the build/buy question is both. Effectively implementing this hybrid approach requires that labs first select a LIMS that addresses their specific science and workflows needs. They then build the parts they are best suit- ed to build. Achieving this requires software that can be configured by scientists and customised by scientific programmers and bioinformaticians using modern, familiar software development tools and APIs.
Software marketing often conflates ‘configura- tion’ and ‘customisation’, but engineers understand they are distinct. Configuration refers to changes in existing software that can be made via the user interface by any user. As mentioned above, some systems offer preconfigured, out-of-the-box set-ups that scientists can use to add new lab methods, col- lect records off a new instrument, or specify a par- ticular sample preparation procedure. Easy config- uration empowers scientists – who best understand laboratory requirements and how the system needs to work – to make critical changes to the LIMS. More importantly, configuration frees program- mers and bioinformaticians to focus on more high- value projects, which typically require customisa- tion. Scientific programmers understand that cus- tomisation is quite simply changing the actual code of software so that it can do something new or dif- ferent. Anyone armed with the appropriate pro- gramming expertise, software tools and APIs can make these types of modifications. Bioinformati-
Drug Discovery World Summer 2011
cians and scientific programmers work best when they have the power and control afforded through systems that let them use familiar tools (such as standard-based architectural styles and scripting languages such as Python, PERL or Groovy) to adapt software to accommodate the unique needs to their labs. Software that supports both configu- ration by scientists and lab technicians and cus- tomisation by bioinformaticians and scientific pro- grammers enables labs to efficiently implement sys- tems that better match their current and future informatics requirements.
Selection criterion #3: Does the LIMS accommodate different users and workflows?
NGS labs require varied expertise to accomplish their objectives. Principal investigators, lab man- agers, lab technicians, scientists, bioinformaticians and scientific programmers all contribute to keep experiments running quickly and efficiently. All of these individuals have different responsibilities, priorities and correspondingly different ways that they wish to view and act on data.
It sounds clichéd, but in a leading-edge next-gen- eration lab, one user interface does not fit all. To work effectively, users require access to all and only the information relevant to their job. Targeted user interfaces in an NGS LIMS should provide a dashboard of relevant activities while also pulling appropriate data from the larger system and dis- playing it to those who need to act on it. Intelligent, targeted user interfaces can aid the fol- lowing types of users:
l Lab technicians. Scientists and technical staff require fast, efficient access to data that helps them track sample status, determine which samples can be prepared together, simplify creation of library pools for multiplexed sequencing runs and access and review past work. Dashboards should help them answer such questions as: “What experi- ments do I need to carry out today?” “What work is coming my way so I can plan ahead?” “Which libraries can I pool together for a multiplexed run?” or “Am I getting good quality data off that run I just started?” l Lab managers. Management dashboards can pro- vide a high level summary of everything happening in the lab—an overview of active project status and instrument performance with the ability to drill down into activities to look at more specific results or met- rics. Managers also require reporting and project management tools to manage client communications, invoicing, and administrative reporting. Interfaces
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