Passing the Baton: Ensuring Reproducibility in Bioinformatics

The fields of medical science, life sciences, and biopharma are highly competitive, with researchers racing to develop groundbreaking scientific discoveries, therapies, and to create new diagnostic tools.

Yet, amidst this competition, there is a deep-seated culture of collaboration. Scientists publish research papers and share their findings, driven by the collective goal of advancing knowledge and improving human health. This openness allows others to build upon existing research, accelerating the pace of innovation.

However, this collaborative ideal is often challenged by a significant obstacle: “the reproducibility crisis.” Despite the best intentions, reproducing complex bioinformatics analyses using new data is often extremely difficult and expensive to do. Researchers who attempt to replicate published results frequently encounter obstacles in recreating the original code and computational environment, leading to inconsistent outcomes. This not only hampers collaboration but also slows scientific progress, as the inability to reproduce results undermines the credibility and reliability of the entire research process.

The Challenge of Reproducibility

Reproducibility is a cornerstone of scientific research. In bioinformatics, where data and computational tools are critical, ensuring that complex pipelines, and the results they produce, can be reliably reproduced by other researchers is essential. Traditionally, when a researcher published their findings, other scientists intending to replicate the results faced a daunting task: They needed to recreate the exact computational environment (software versions, complex code, parameter settings, and more) which enabled the original analysis.

This can often involve installing and configuring any number of software packages and dependencies — specific versions of tools, libraries, and scripts that needed to be perfectly aligned with the original setup. Even minor variations can lead to different results, making true reproducibility difficult to achieve. The process was further complicated by the need for admin access, as well as in-depth technical skills and knowledge, which many researchers might not possess. In such cases, they would need to rely on specialized IT support and development assistance, adding more steps, costs and time which delays and slows an already complex process.

This lack of reproducibility not only slows down scientific progress but also creates barriers to collaboration. When researchers can’t easily reproduce each other’s work, it becomes harder to build on previous findings, ultimately slowing the advancement of knowledge and innovation.

Streamlining Reproducibility with Via Foundry

Via Foundry is designed to address this critical issue. The platform simplifies the process of sharing and reproducing complex bioinformatics pipelines, ensuring that other researchers, with whom you want to share, can easily replicate results without getting bogged down in the myriad of technical issues just described. There’s no need to worry about installing specific software versions, duplicating code or configuring complex environments — Via Foundry handles all of that behind the scenes, leveraging both its own native capabilities and containerization technologies like Singularity and Docker. These containers, which can be attached to an entire pipeline, individual modules, or even specific processes, ensure that the exact computational environment is preserved and can be replicated across different setups. The result is pipelines and methods can now be seamlessly shared and results duplicated through private repositories or public platforms such as Quay, DockerHub, or GitLab.

With Via Foundry, sharing a pipeline is as simple as providing a link. Whether through direct sharing or GitHub integration, the platform allows other researchers to run the pipeline with their own data seamlessly. Researchers simply set their parameters, and the pipeline executes as intended, ensuring consistent and reproducible results.

Additionally, Via Foundry excels in project management with its extensive event-based metadata features. The status of every step in a project can be tracked meticulously. For instance, when library preparation is completed, the status can be automatically updated, and samples sent to the sequencing facility can be tracked using barcoding systems for larger projects. Once sequencing is done, and raw files are uploaded to the preferred storage (whether cloud or on-premises), the pipelines can be automatically triggered, quality checks performed and the status updated to keep users informed of the progress. This level of flexibility ensures that every aspect of managing omics projects, from beginning to end, is streamlined and transparent, further supporting collaborative efforts and efficient research progress.

This streamlined process not only saves time but also removes the technical barriers that have traditionally hindered reproducibility in bioinformatics. By making it easier for researchers to share and replicate each other’s work, Via Foundry fosters a more collaborative and productive scientific community.

Why Reproducibility Matters

Reproducibility is not just a technical necessity — it’s fundamental to the credibility and reliability of the entire scientific enterprise. When research findings can be reliably reproduced by others, they gain legitimacy and can be confidently built upon. In fields like life sciences and biopharma, where data-driven discoveries are rapidly advancing our understanding of complex biological systems, ensuring reproducibility is crucial for translating research into real-world applications, such as new therapies and diagnostic tools.

Via Foundry’s focus on reproducibility not only enhances the rigor of scientific research but also democratizes access to cutting-edge bioinformatics tools. By making these tools more accessible and easier to use, the platform empowers a broader range of researchers to contribute to the field, driving innovation and discovery forward.

Conclusion: A Smooth Baton Pass in the Race for Scientific Discovery

In the race for scientific discovery, reproducibility is like the baton in a relay race — it must be passed smoothly from one researcher to the next to ensure collective progress. Just as a misstep in a relay can cost precious seconds and disrupt the team’s rhythm, a lack of reproducibility can hinder collaboration and slow the advancement of knowledge.

Via Foundry ensures that this baton is passed seamlessly, allowing researchers to build on each other’s work with confidence. By addressing the reproducibility crisis and enhancing project management, Via Foundry supports a more collaborative and innovative research environment, where every discovery contributes to the shared goal of advancing science and improving human health.