Why Am I Sick? With This Tool, Doctors Could Know At a GlanceAll too often an answer to the simple question of “what is making me sick?” does not come easily. Current methods for figuring out what viruses or bacteria are causing infection come with…
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June 02, 2016
Health Sciences
Innovation Interviewer: A new tool that could completely change how we diagnose infectious diseases, up next on The Scope. Announcer: Examining the latest research and telling you about the latest breakthroughs, the Science and Research Show is on The Scope. Interviewer: I'm talking with Gabor Marth, professor of human genetics at the University of Utah and co-director of the USTAR Center for Genetic Discovery. Diagnosing infectious diseases is still a significant problem in medicine. Right now in the clinic, you either do a culture or maybe a PCR test to see what's infecting a person. You have co-developed a tool called Taxonomer that's taking a completely different approach. Gabor: Taxonomer is a software tool that is able to look at DNA fragments, which is what current technologies are able to produce from blood from an infectious disease patient, and identify the organisms that are present in that sample. These types of tools, in my opinion, are very likely to replace the tests that you mentioned, that are based on specific hypotheses. We have to know what the strains that we are looking for in these patients, whereas tools like Taxonomer will be able to look at the DNA sequences and tell you upfront what pathogenic organisms are causing the patients disease. Interviewer: So if you have a patient that's sick, you take a little blood, you have to get the DNA from that blood sequence for all the genetic material, I guess. And then that sequence information goes in the Taxonomer, and Taxonomer catalogues everything that's in there. Gabor: Yes, as you mentioned, in traditional clinical tests you would have to ask "Does this patient have this particular strain of, which specific pneumonia strain this particular patient has." Sometimes these experiments fail. Some of the strains go better in the media that are used in laboratory tests than others. When the same data goes to a Taxonomer you just get an unbiased view of which strains and what proportions are present in the patient. That will help the physician diagnose the patient much faster, and in a much more objective manner. Interviewer: So there are some really stand-out characteristics of Taxonomer. These are based on the software called Iobio, which is what you developed, correct? Gabor: Taxonomer itself is the engine, it is the software that is able to take a DNA fragment and tell you which organism that DNA fragment presents. And it's married to Iobio, which is a web-based analysis platform that my laboratory is developing, that allows interactive, real-time and high visual representation of the data. Interviewer: So yes, one way I've heard it described is that it's like putting a super computer in the hands of your average user, it has that much power behind it. But it's accessible on the internet. Gabor: This is actually an accurate description because the computational power that allows Taxonomer to run is enormous but all that is hidden from the user. It's what's called the backhand of the architecture, there is a powerful computer sitting in the background that performs the computation in very, very intensive classification job. But what the users see is almost immediate response and almost immediate results. Interviewer: And so before, this type of analysis took a lot longer and probably had to be done by a specialist, right? A bio-informatic specialist. But now anybody could do it. Is that the idea? Gabor: Many, many things that the average user will be able to do. Of course, this is not to say that there is no longer need to for a . . . Interviewer: We don't need you anymore. Gabor: More involved analysis and expert analysis, but what Taxonomer will be able to do, it will be able to give a scientist, or even a lay-person, an immediate view of what is the overwhelming characteristics of the data. For example, we have examples of an Ebola patient. And when you look at the viral composition of the blood taken from this Ebola patient, you will see that pretty much 100% of the viral load in this individual is Ebola. So that's a very, very obvious and easily interpretable answer to the question of what's making this person sick. Interviewer: Well like you said, a lot of the strength of this tool is that it's very visual, and that helps people take in information in a different way. Can you talk about that a little bit? Why you think that's an important component. Gabor: That's how the human mind works. Experts can be trained to look at large data files and textual outputs coming from software and interpret that data in a scientifically meaningful fashion. But our human brain doesn't quite work that way. We like to see things, we like to use the brains innate analytical abilities to start from an image to develop an understanding. And that is the underlying philosophy behind the Iobio project. Interviewer: In a few years how do you envision Taxonomer, in particular, being used? Gabor: I view this that its applicability is going to be very wide. This is going to be a very wide and generally applicable tool. Some of the applications that we can foresee today will be infectious disease identification in the clinic that will require expert review of the data. Moving forward, the obvious application will be pathogen identification in the field, under field conditions. Once the technologies are developed for portable and faster DNA sequence can be used under field conditions. This is only scratching the surface, checking sanitary conditions in restaurants and many applications that we can think of now and many even more applications that will become clear in the future. Announcer: Interesting, informative, and all in the name of better health. This is The Scope Health Sciences Radio. |
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Science Insider: Bam.Iobio App Puts Sequence Alignment Inspection in the Hands of ResearchersBam.iobio is the first app of its kind that allows scientists to analyze genome sequence data on their web browser, interactively, and in real-time, without having to rely on terabytes of storage and…
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November 25, 2014
Health Sciences
Innovation Interviewer: We're talking about Bam Iobio, an easy to use web-based app that analyzes genomic sequence data in seconds. Announcer: Examining the latest research and telling you about the latest breakthroughs, the Science and Research Show is on The Scope. Interviewer: I'm talking with Dr. Gabor Marth, professor of human genetics at the University of Utah. Dr. Marth, your app, called Bam Iobio, was just published in "Nature Methods." Why are you so excited about it? Dr. Gabor Marth: Super excited about Bam.iobio because this is the first app that shows off the capabilities of this new interactive genomic ecosystem that we are building here at the University of Utah. Interviewer: Tell me, what is Bam Iobio? What does it do? Dr. Gabor Marth: In a Bam file, you're communicating sequence alignments. That's the data that's generated by the sequencing machines and is the common currency of every type of genomic analysis. Interviewer: So, this is kind of a first step. When you get your genomic sequence data back, you're checking it over to make sure that it's the quality you need and the coverage that you need. Dr. Gabor Marth: That's the very first step. This is something that every researcher should do before they start analyzing the data any further. Interviewer: How does this compare to what was available before? Dr. Gabor Marth: Instead of doing genomic analysis end to end that would normally take days, weeks, and sometimes over a month, and require lots of computational resources and data storage and computer clusters, etcetera, the user just uses a laptop computer browser and is able to look at that part of the data that's important to them within a few seconds. Then further explore, go back and forth, change analysis parameters, etcetera, and redo analysis in real time as many times as they want and develop a real connection to the data that they analyze and the tools they use. Interviewer: So, it's kind of like going from one of the first Apple computers to an iPhone 6. Dr. Gabor Marth: Well, that's a very flattering analogy but not entirely incorrect. Interviewer: You know, if you do that comparison, that sort of iPhone 6 interactivity has been around for a while now, five years or so, why do you think it's taken so long for this type of analysis to catch up? Dr. Gabor Marth: Genome scale, the ability to generate data on the scale of genome at ever decreasing costs, very cheaply today, has taken the community by surprise. The developer community focused on being able to analyze the data in its entirety and develop algorithms that are able to deal with the data on the scale that is produced today. That was the first impetus. Interviewer: Who is this app designed for? Dr. Gabor Marth: Bioinformaticians, core facilities that deliver data to other researchers, and researchers themselves. You pay for data. You get your data back from your core facility. The first thing you can do is check out the data quality. Interviewer: These are part of a larger plan that you have. Dr. Gabor Marth: In fact, we just completed a second app very similar in nature that allows you to look at genetic variants. This app is called vcf.iobio.io. It looks at VCF files. These are the files that programs create with genetic variants that they find, for example, in an individual human genome. This app, very similarly to bam.iobio, gives you overall genome-wide metrics, chromosome-wide metrics, or regional metrics of your file, things that are important to assess whether your variants are properly called and give you some regional understanding of your variants as well. Interviewer: You're encouraging developers to tinker with Iobio. Dr. Gabor Marth: Yes. What we are focusing on now that this paper is out is to develop the tools that will enable other developers to build genomic analysis apps of their own. Currently, to develop a genomic analysis app, it takes a long time, because you have to write pretty much everything from scratch. We'll be making libraries available that a developer can use to use what we call the Iobio platform. That is the type of software libraries that a developer needs to put together a prototype app maybe in a day and a more polished app in a couple of weeks. Announcer: Interesting, informative, and all in the name of better health. This is The Scope Health Sciences Radio. |