Technological advances and cost reductions in genomic sequencing technology have rapidly increased the rate, ease, and diversity of sequencing data collection. This revolution has transformed life sciences into a data centric field making modern biomedical research heavily reliant on advanced computational techniques that require researchers to have a working knowledge in computation to be effective.  

Unfortunately, the capabilities needed to gain insights into biology and disease from sequencing data have not benefited from the same rapid expansion as generating the data. The variety and complexity of computational tools creates a high barrier for non-specialists and as a result a large portion of the data produced is never analyzed, is analyzed improperly, or takes an extraordinary amount of time to analyze.  

To learn more about the transformation of biological research see How big data is changing science

To gain biological insights from data, the barriers to finding, understanding, and using current proper analytical techniques must be significantly lowered.

We have created a central knowledge repository designed to house the workflows, tools, and data the bioinformatics community is using and intuitively illustrate how the community is using them. We believe the best way to learn is by example and through feedback, and that examples should be presented in an accessible and understandable way.

Truwl is designed with the following concepts in mind:

• Truwl is platform-agnostic: It doesn’t matter where you run or create your tools and workflows and store your data. They are presented and distributed in a uniform way.
• Truwl’s content is self-explanatory: You shouldn’t have to read through a bunch of documentation to use something and figure out what it does.
• Truwl facilitates open dissemination: Bioinformatics content must be findable. To us ‘findable’ doesn’t mean you can access it if you know where to look. It doesn’t mean looking around the web for files with the right extension or creating an account on a private platform before you can have a look around. “Findable” means you should be able to find things with a search engine (Google) and you can browse to your heart’s content without signing in. We’ve put in extra effort to make Truwl search-friendly so you can find what you’re looking for, even if you’re not sure what it is you’re looking for when you start out.  And, if you are a content contributor, “findable” also means that by using Truwl your analysis methods are available to the community through a search-engine-optimized platform.  Truwl’s architecture helps contributors maximize their reach and gather as much feedback as possible both through internal community-focused tools and external search engine capabilities.  If your content is on Truwl, you benefit from the feedback of the Truwl community, but it’s also findable by users who do not use Truwl.  
• Truwl’s content is ready to be used: The content you see on our site isn’t just for looking at. Workflows and tools are backed by CWL and WDL files that are actually runnable. Truwl’s pages that describe data files actually store the location(s) of that data so you can look at it and use it--if it’s public or you have the right permissions.
• Truwl is accessible, understandable, and thorough: Because Truwl is designed as a modern web application, it only requires a web browser to function and there is no software to download. Truwl presents complex workflows and content through a modern Javascript-powered front-end to create a familiar and intuitive user experience. At a glance, Truwl allows you to see how bioinformatics analysis tools are connected together in workflows through an interactive graph.  Users are presented with visuals that allow them to quickly understand the complex operations within a workflow without getting bogged down in YAML and JSON files.  
• Truwl’s content is explorable through relationships: Linked records allow for exploration of relationships between workflows, tools, and files. Workflows are made from sets of tools; tools and workflows use files for inputs and outputs. Because Truwl exposes the relationships between these elements, it’s simple to explore the tools that are used in a workflow or see what tools and workflows have used a particular file as an input.  All these relationships, and more, are exposed through simple and familiar interface elements like links and tooltips, so that you can easily navigate complex hierarchies of interrelated information. In addition to the direct relationships between workflows and specific files and tools, any of these items can also be tagged to easily allow users to find other related content. Through the use of tagging and intuitive search tools, a user can quickly locate all of the workflows on Truwl that are related to their field of research. Truwl exposes these relationships so you can quickly explore information that you may not have even known was relevant to your own work. 
• Truwl is beneficial for content creators: Truwl makes it beneficial for community members to share their analysis methods. By sharing on Truwl, you have access to the widest possible audience with the most purpose-built tools for providing immediate feedback. You can get feedback from the community through commenting sections before or after implementing your methods (think of it as a method’s preprint!). Make your tools and workflows better and avoid - or at least be aware of - mistakes or weaknesses to your approach. Tool creators can see how their software is used by the community as a standalone tool and is incorporated into workflow or scripts. Get credit and gauge how useful your work is to others through looking at how often it’s used and through community voting.

Truwl, started as a result of a lot of ‘what ifs’.  Co-founders Karl Sebby and Tim Thompson previously worked together on a cancer research project. When it came time to make plans to gather sequencing data and put together a data analysis strategy they dove into the scientific literature to see what the state of the art was and how to best use it to make new scientific advances. 

After months of reading methods sections, reading software documentation, and downloading and trying programs, little actual progress was made. All we wanted to see was what programs were used to process data, what were the parameters and what were results so we could start implementing our own analyses. 

We found out that figuring out how best analyze sequencing data is a significant problem that needed better solutions. What if things could be easier? What if methods were shared in a way that others could rapidly find and see what others have done and use it as is or adapt it to suit their needs? Could research be done faster, new ideas tested more quickly, more companies started from people analyzing public datasets to make discoveries into rare diseases that are understudied? What if patients with their own sequencing data could gain insights about themselves and pass the results onto researchers and clinicians? The more we thought about it, the greater the possibilities seemed. What if graduate students and postdocs could analyze their own data quickly with confidence with community support without having to become computer science experts? What advances could be made in medicine, diagnostics, agriculture, conservation, and a host of other fields that are using sequencing data to understand biology? 

This was the start of the development of Truwl to allow researchers to start and stay at the cutting edge of genomic analysis.

This is just a short summary of who we are and what we do since we prefer to write code and learn about the latest science much more than writing ‘About Us’ pages. But if you want to know more feel free to email us at info@truwl.com with any specific questions, to propose a collaboration, or just introduce yourself. 

If you’re lucky enough to find yourself in our neck of the woods (northwest Montana) we’d be happy to sit down with you and have a chat. If one us happens to head out into the wider world for a meeting, conference, etc. we’ll usually announce that with a tweet (@xDBio_Inc).