What is Bioinformatics as a Service?

At Genevia, we analyze omics data and build tools for exploring insights from high-throughput experiments. We provide our time and bioinformatics expertise as a service, and call our product just that: Bioinformatics as a Service. What does this mean, and how is Bioinformatics as a Service different than hiring a bioinformatician of your own or collaborating with academic bioinformaticians?

Removing a bottle neck instead of creating one

Perhaps you are an investigator with a research question calling for omics measurements, such as next-generation sequencing (NGS) or mass spectrometry. You may wish to discover the mechanism of action of a drug, variants associated with a particular disease, biomarkers to predict treatment response, virulence-associated genes in strains of bacteria, or new subtypes of cells within a complex tissue. When thinking of the project as a timeline from a hypothesis to published findings, at which stages and what type of bioinformatics support is needed?

The figure below represents the five stages of a project in which Bioinformatics as a Service can drive your research forward. There is a natural progression to these elements which is also cyclical as results are reassessed and new research questions arise.

Your specific needs will determine how we can help you. You can choose to collaborate with our team in the planning phase, active data analysis phase or the interpretation and publishing phase.

In research involving omics experiments, the most intensive bioinformatics work takes place after identifying the molecules or variants that differ between sample groups. It is this downstream analysis which helps you get from lists of mutations, genes, or pathways to new insights. A bioinformatics service that only provides lists of results wihtout tailored downstream analyses is more likely to create a bottleneck than remove one. At Genevia, we believe a well-designed bioinformatics service can bring you from raw data — or even better, a research question — all the way to publication.

Therefore we complement the more basic upstream analysis with downstream analysis, which may include:

  • pathway, network and gene regulation analyses,
  • integrating different data modalities (e.g., transcriptomics and epigenomics) to gain deeper insight about a biological system,
  • leveraging machine learning to predict phenotypes or clinical outcomes from molecular data,
  • analyzing public data sets with similar experimental settings,
  • reanalyzing the data with different approaches to ensure the findings are robust,
  • visualizing the data to enable interpreting and communicating the results,
  • wrapping up the analysis workflow as a pipeline for future use, and
  • a lot of discussion between the dry-lab and wet-lab teams to enable drawing conclusions from the outcome.

Bioinformatics analyses might not be performed at all stages of a research project, but having bioinformatics support readily available is valuable at all stages of the process, from experiment design all the way up to replying to manuscript reviewers’ comments and depositing data and code to repositories. On-going bioinformatics support service ensures that you get help whenever needed.

Service mentality

Taking advice from experts is never a bad idea. In fact, we believe it can save a lot of time and resources while increasing quality. We do the same when we need help with financial reporting or we have a need for professional level marketing knowhow. External service providers focus on your needs, allowing you the freedom to perform your research. What does service mentality then mean? In practice, there should be trust that the service provider will always think of the client’s goals before their own, and the job is not complete until the client is satisfied.

In terms of service quality, you need to be able to trust your service provider has both access to, and good command of, the best possible tools and methods which fit your bioinformatics needs. Often that’s something only a team of bioinformaticians can offer, since every one of them has their own skill set and experience. Using the latest tools and methods is especially important in the rapidly evolving field of bioinformatics, where even slightly outdated methods can produce results which are significantly different, or even incorrect.

Equally important is that once results have been produced, they need to be explained in such a way that you can understand what has been done and why. Otherwise they are uninformative and cannot be integrated into your research or address your research question. Thus, consistent and clear communication is key for success.

How are the projects managed?

Many researchers believe that any bioinformatician can perform any bioinformatics analysis, or tackle all of the analyses in a research project. Naturally, just as no wet-lab scientist can do every laboratory experiment, this is not how it works in practice. Bioinformatics is an exercise in teamwork like any other scientific endeavor.

To ensure the best possible outcome for your data analysis needs, you need to have professionals competent in subjects from molecular biology to data science and in skills ranging from software engineering to project management. Together, the right collection of professionals can create a team that will tackle any bioinformatics challenges imaginable, but just like any other highly talented team, it needs someone to guide their direction. At Genevia, we call that person a project manager.

Project management is there to ensure people do the right things in the right order. This means that no resources will have been wasted. When the project is done, whether it’s biology, programming or wet-lab work, communication and documentation is tantamount to success.

A project manager transforms the client’s needs into discrete tasks for bioinformaticians and programmers. The project manager is the client's voice and he/she makes sure that the client gets the results they need. In the process of doing so the project manager keeps the whole project on track and reports what has been done, how it has been done and, importantly, what could be done next. In addition, the project manager ensures that results (files, tables, figures, and code) are understandable by the client and collects all the results together into a publication-ready project report.

The workflow

The scientific content of each project is unique, but the workflow — especially for our academic customers — follows a standard pattern.

1. Experiment design

First we discuss your research and propose any experiments (e.g., NGS) and bioinformatics analyses that would suit your needs. We will then draft an analysis plan and discuss your research target.

2. Data generation

We can help you acquire NGS experiments from the most convenient and cost-effective sequencing service provider. If you already have the data, we may skip this phase and move straight to the next one.

3. Basic analysis

After receiving the data a dedicated project manager reviews the files and background information, such as publications, and schedules a kick-off meeting to agree on the first steps before starting the actual analyses. Unless we receive quality controlled (QC’d) data, we perform a thorough QC analysis for all samples, summarize and report the data quality to you, and discuss any possible quality issues.

After ensuring data quality, we run an analysis pipeline to, e.g., assemble the genome or transcriptome, estimate gene expression levels, or find genetic variants or epigenetic events. The genes, loci or variants are annotated, statistically compared between sample groups, and visualized. We present these preliminary results to you in a teleconference and agree on the downstream analyses. If your data has already been processed to this level, we may begin at the downstream analyses.

4. Downstream analysis

More tailored analyses are run to answer your research questions. As described in more detail above, this step typically involves pathway and regulation analyses, integrating different data types, comparing your data to publicly available data sets, and associating molecular events to biologically or clinically relevant variables using regression and machine learning techniques.

5. Interpretation

After performing the analyses, we sit down with you to carefully explain what we did and what the results mean. After presenting the results, we might still reformat or modify the figures and tables according to your wishes. We then provide you with a project report including result tables, figures, and descriptions of the methods.

We can provide assistance in the manuscript preparation and submission phase as well. Rerunning analyses, reformatting figures to comply with the guidelines of a specific journal and writing methods descriptions are the typical needs in this step. Eventually, if manuscript reviewers have bioinformatics-related questions, we can address them by elaborating and justifying the computational methodology.

Conclusion

Naturally, it’s not only the combination of some skilled individuals and good project management that is required to successfully complete a project: building a cohesive team and setting up the right tools and computing infrastructure takes time. For example, we at Genevia have used thousands of hours to develop our analysis pipelines and set up our computing infrastructure to ensure all of our tools stay in good order and are consistently accessible to our bioinformaticians. The pipelines and automated processes are refined over time and updated as new algorithms and methods arise.

During the 9 years Genevia has been at work, and collected from running more than 200 successfully completed projects, we have learned that experience is the key factor in project management.

In summary, Bioinformatics as a Service provides the needed expertise, tools, and results to not only complete, but also plan and significantly enhance your research projects. Because we possess a team of bioinformatics specialists with a wide array of skills and experienced project managers, Genevia is able to assist both corporate and academic customers in critical large scale projects. Collaborations can be either a single project or on a continued basis, and we are able to assist at any point in your process, whether you are in the planning stages or adding analyses to an ongoing project. A comprehensive Buyer's Guide is available which further explains needs and requirements when using Bioinformatics as a Service.

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