As a Principal Investigator (PI) or group leader, you may find yourself leading a project with a significant bioinformatics component, even if your own background is primarily in experimental science. The question of whether to handle bioinformatics work locally (e.g., through trainees or in-house staff) or outsource it to an external bioinformatics consulting provider is one that many researchers — in both academia and industry — wrestle with. This article is based on recurring conversations we've had with academic researchers and is intended to help you think through your options with clarity and balance.
Quick Navigation
- When you should use local personnel (Part 1)
- When you should use local personnel (Part 2)
- When outsourcing makes more sense
- How to choose a bioinformatics service provider
- Is local collaboration a good option?
If you're at an academic institution and part of your mission is to train students and postdocs, then building in-house bioinformatics capacity is a logical step. Particularly for labs funded by training grants, outsourcing may not be allowed or advisable.
Yes, it may take longer, and yes, it may cost more when considering the time investment and the learning curve. But this is true for many other parts of research - training is a long game. Helping your trainees overcome technical challenges and acquire bioinformatics skills is an investment in your lab's future.
Building this capacity internally can also give you more flexibility in the long run. Bioinformatics is becoming increasingly central to life sciences research. Having even a basic local capability can make your lab more self-sufficient and responsive.
Many faculty worry whether they can adequately guide students diving into bioinformatics. That's understandable, but students today often learn technical material more independently, leveraging online resources and community forums.
That said, not every trainee is well-suited to bioinformatics. It's important to assess interest and aptitude.
- If a student shows enthusiasm and a willingness to learn independently, it may be worth letting them try.
- But be prepared to step in early if the project stalls.
This option works best when the primary goal is training and long-term skill-building, not immediate turnaround or guaranteed accuracy.
Sometimes, quality, cost-efficiency, and speed are higher priorities than training. This is especially true for:
- Projects involving complex or custom bioinformatics components
- Work beyond the scope of basic pipelines or public workflows
- Tight deadlines for manuscripts or grant submissions
Bioinformatics is well-suited for outsourcing, especially when working with external bioinformatics services that offer secure data handling and flexible analysis options. It deals with digital data that can be securely transferred and processed remotely. Unlike wet-lab components, no physical shipping or specialized onsite equipment is required.
In some cases, outsourcing can save you both time and funding - especially when compared to training someone internally for a one-time task.
If you do decide to outsource, vet the provider carefully. You're trusting an external group with a key part of your research. Look at:
- Credentials and experience of the bioinformaticians
- Examples of similar projects they've done
- References from past clients
- Their understanding of your broader research aims
Don't choose based solely on price or promises. Be wary of deeply discounted quotes from providers with unclear qualifications.
Bioinformatics is in high demand, and training programs can't always keep up. It's not uncommon to find inexperienced analysts being assigned critical tasks in some core facilities or startups. A wrong decision here can waste funds and delay your project significantly.
At many academic institutions, you may have bioinformatics faculty nearby. Collaborating with them could be a great option, if there's natural synergy.
- Check whether their research interests align with yours.
- If you're generating data that fits well with their analytical focus, collaboration may benefit both sides.
But collaboration is different from service. If you primarily need someone to process your data on a set timeline, collaboration may introduce friction. Consider potential misalignments in:
- Authorship expectations
- Timelines vs grant deadlines
- Focus on method development vs your biological questions
Academic collaborations can be productive, but they also come with trade-offs. If your priority is reliable, efficient data analysis without additional negotiation, a service arrangement may be better suited.
There is no one-size-fits-all answer to the question of local vs outsourced bioinformatics. But by understanding the trade-offs, assessing your own lab’s or team’s strengths, and carefully selecting collaborators or bioinformatics service providers, you can find a path that supports both your scientific and logistical needs.
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