We're going to go ahead and get started. I'm Tycho Peterson. It's my pleasure to introduce our next company this afternoon, NanoString. Just a quick reminder, if people do have questions, to submit them through the website. With that, let me turn it over to Brad. Thanks, Tycho, and thank you everyone for taking some time today to hear about NanoString. This is an exciting moment for our company. The scientific community has begun to recognize the importance of spatial biology and NanoString's leadership in the field. Last month, we held an Investor and Analyst Day during which we unveiled our vision for spatial biology, including expanded TAM estimates and a more detailed product roadmap. The year ended on a high note as Q4 exceeded the top end of our guidance range, with beats across both GeoMx and nCounter. During the first week of this year, Nature Methods recognized spatial biology as its Method of the Year. The year is set to get off to an even more exciting start in the months ahead as we launch our GeoMx Whole Transcriptome assay and engage more customers on our Spatial Molecular Imager. Today, I'd like to review our performance for 2020, recap some of the highlights from our recent Investor Day, and lay out the catalysts and strategies that will drive our growth in 2021. I will be making some forward-looking statements throughout the presentation, and I'd refer you to the risk factors in our SEC filings. Starting with a quick recap of 2020, earlier this week, we summarized strong top-line results for the fourth quarter and the full year. We ended the year with product and service revenue about $2 million above the top end of our guidance range, with about half a million dollars of the beat at the top end on nCounter and about $2 million on GeoMx, driven primarily by strong consumable revenues for GeoMx in the fourth quarter. Over the course of 2020, spatial biology demand more than offset COVID-19's impact on nCounter, resulting in strong Q4 revenue growth for GeoMx of 44% year-on-year and a total growth of 200% for the full year, to more than 200%. We're particularly excited about the GeoMx pull-through, which doubled sequentially. Our nCounter core business finished the year strong off Q2 lows that were impacted as labs closed during the year, and we ended up with an 11% sequential growth of nCounter in the fourth quarter. nCounter at this stage has returned to about 90% of its normal strength off the Q2 COVID lows. Overall, we're pleased that spatial biology was able to drive continued growth in 2020 despite COVID headwinds. Moving now to the next slide, let me summarize the full achievement and successful achievement of our 2020 strategic objectives. We set out to do four things this time last year, and I think we achieved all of them. First, we looked to accelerate GeoMx adoption in translational research and second, expand GeoMx into discovery research using our NGS readout. We were actually able to achieve during the course of 2020, the top end of our full year guidance range for GeoMx revenue, despite the fact that COVID-19 occurred. We achieved our pre-COVID revenue guidance on GeoMx, so we feel absolutely great about that progress. In addition, we set out to select applications for our Hyb & Seq chemistry that resulted in the revelation of our Spatial Molecular Imager and the extension of our roadmap in spatial biology. Finally, we set out to maintain momentum in our core nCounter business. As I've already summarized, we're pleased with how that business has recovered from the COVID-19 lows of mid-year. In addition, and perhaps more importantly, as outlined on the next slide, we described a new mission for NanoString in recent months, and that is to map the universe of biology. This organizing principle describes the impact that we think we can have through our spatial biology offering, as well as the extension of our impact beyond the traditional core and translational research in oncology to virtually all aspects of biological research. Going to the next slide, we're not the only people to recognize the importance of spatial biology. Early this year, Nature Methods named spatially resolved RNA the Method of the Year. Nature has a pretty good track record of calling the next big trends in biology. They actually highlighted four things in the numerous papers that were included in this issue, four things that really underpin and support our strategy. The first is spatial biology is clearly fundamental across all areas of life sciences, not simply discovery research, not simply translational, not simply the clinic, but all of it. Second, it is clear that there is going to be two different product categories in this field of spatial biology, one built around multicellular profiling and the other built around single-cell imaging, and I will describe that in more detail in a moment. Third, it is key that multiple analytes, meaning both proteins and RNA, will be critical analytes in this field, and NanoString has built great capabilities on both. Finally, while there are many different approaches today for spatial biology, most of them remain what you might call home brew methods in single academic labs in desperate need of prioritization, and NanoString is focused on helping these new techniques become widely applicable and automated in customer labs. There really couldn't be a better way to start the year than to declare that spatial biology is the next revolution in life sciences. As the next slide shows, we think of spatial biology as the third wave of genomics. If you think about the tissue that we're all made up of as a fruit tart that has physical structure and a number of different cell types that are analogous to the fruit on top of a tart, most of genomics has historically been bulk genomics, which is the equivalent of grabbing that fruit tart, dropping it in a blender, and creating a smoothie. While you can taste that smoothie very easily and try to infer the different number of bananas and strawberries, et cetera, you clearly lose a lot of important context through bulk biology. The next revolution that happened after bulk biology and the invention of the next-gen sequencer was single-cell biology. You can think about single-cell biology as effectively plucking the fruit off the top of the tart and looking at it on an individual basis. 10x Genomics, with their Chromium system, really led this revolution about seven years ago by capturing cells in droplets and allowing them to be analyzed on sequencers. Today, though, the movement is towards spatial. We need to understand, and researchers need to understand where each of those fruit is actually located on the fruit tart in order to understand the full richness of the structure and, by analogy, how the cells are interacting with each other and actually building a tissue. Spatial biology on the next slide, we describe that spatial biology as a revolution is going to span everything that happens in life science. In discovery, we're going to be able to move from the abstraction of t-SNE plots generated by single-cell sequencing approaches to actually showing cell types in their spatial context. In translational research, high-plex spatial technologies are going to eliminate the need to run large number of slides from the same sample by allowing people to highly multiplex a large number of markers on a single slide. Finally, in the clinic, we expect that spatial biology will move away from bulk biomarkers that are highly imperfect average measurements that predict response to drugs to precise spatial biomarkers that tie expression of markers down to single cell types or single compartments in a tissue. On the next slide, we show that also that spatial biology is likely to happen at three different levels of resolution, and these are highly analogous to when you think about using a map. At one level, researchers and clinicians are going to want to look at whole tissue slides, seeing the general morphology and general expression of an overall tissue biopsy. At another level, just like zooming in on a particular neighborhood in a city, we'll want to look at regions on the order of tens and hundreds of micrometers and understand what's going on in the different neighborhoods in collections of cells in an overall tissue biopsy. Finally, from time to time, we're going to want to zoom in on a single address, finding a particular cell and understanding exactly what it is doing. This provides multiple different product categories and opportunities across all of spatial biology. As the next slide shows, we've mapped spatial biology on these two axes. One, resolution, as I just described, and the second is plex, which is the number of different targets that a researcher or a clinician wants to look at at once. Most of the history of science has lived in the bottom of this Y-axis at just one or two or three, four markers at once, but increasingly, spatial biology techniques are allowing researchers to look at hundreds and then thousands, and then the whole transcriptome worth of biology all in a single experiment. We studied carefully the overall demand and market potential across spatial biology, and we've characterized this marketplace, as the next slide shows, at a $12 billion spatial TAM. Now, this is about $6 billion in research TAM and about $6 billion in clinical TAM. Today, NanoString is primarily focused on exploiting that research opportunity, but we believe a diagnostic opportunity could evolve in the future. As the next slide shows, we divide the overall market map into two different product categories that are complementary. Profilers are techniques that look at multicellular resolution, so measurements of 10 to 100 µm at once and can go all the way up to whole transcriptome in plex. Imagers look at single cells and subcellular compartments spatially, and today they go to the hundreds or thousands of plex, but not quite yet the whole transcriptome. Our extensive market research suggests that researchers and leading institutions need both of these capabilities and that the experiments that you will do on them will be different and complementary in nature. I'll use this framework to talk you through our overall product roadmap, beginning with the GeoMx Digital Spatial Profiler. As the next slide shows, the GeoMx DSP is really the market leading platform in spatial profiling. We launched this about two years ago to bridge the gap between microscopy, the traditional microscopy and imaging, and gene expression profiling that's been done over the last couple of decades using genomics tools. GeoMx allows users to select multicellular regions of any size and shape, and then deeply profile the RNA or protein expression in a way that's customary. On one hand, GeoMx appeals to pathologists who've always done spatial profiling and are now looking for higher plex. On the other hand, it appeals to genomic researchers who've traditionally used heat maps like those shown on the right of my slide. Are moving into the spatial for the first time. GeoMx is simple and robust enough to allow both of those customer bases to be comfortable with adopting it as a new technique. How does GeoMx work? The next slide shows the processing of a tissue slide and the readout of the molecular barcode analysis on a subsequent instrument. What GeoMx provides is the opportunity to take a glass-mounted slide of tissue, to stain it in a way that's totally customary for RNA in situ hybridization or immunohistochemistry, to load it on the GeoMx DSP instrument, to select the regions, and then to prepare the samples from those regions for subsequent readout. When we first launched GeoMx, it was available for readout on our nCounter Analysis System that provided about 96- plex worth of readout capability, and more recently, in August of 2020, we opened up the technology to read out on Illumina next-gen sequencers, which provides up to 20,000- plex of readout capability. As the next slide shows, GeoMx serves three distinct market segments, and these segments have differing needs. The translational researcher is focused on disease biology. He or she is likely located either in a biopharma company or an academic medical center. Very often, they're working on FFPE samples with a protein readout, and for them, the nCounter Analysis System provides the right readout capability. There are discovery researchers, typically located in academic settings and focused more likely on genomics or RNA as the primary readout capability. These researchers are less likely to know what targets they're looking at, the high plex capability of NGS is useful for discovery researchers. Finally, in the medium or long term, clinical labs are likely to adopt spatial technologies. These would be in academic medical centers or commercial settings. Almost certainly, they're working on formalin-fixed paraffin-embedded tissue using some combination of RNA and protein. It remains to be seen precisely what the targets are that they're going to be looking at. Certainly, the aim of translational research is to ensure clinical utility in the long run. As the next slide shows, GeoMx is uniquely positioned to meet the needs of these diverse customer sets by providing flexibility and automation. GeoMx has always been flexible in terms of the type of tissue, whether it's formalin-fixed paraffin-embedded tissue or fresh tissue, the size and format of the actual tissue slice, and that has been a tremendous advantage for us as we launched into translational research. Importantly, it's by no means the only advantage. In addition, we are uniquely able to look at both RNA and protein at high plex, which is critical for both discovery and translational research. We have the ability to focus in our technology's power on specific biological structures and regions of interest that our users have defined, and we have the flexibility to go from just a few targets all the way up to the whole transcriptome, allowing customers to dial in exactly the spending and the targeting of the technology in the way they want. Finally, the automated solution of GeoMx provides the capacity to process 10 or more slides per day, and therefore, the ability to scale up to large studies such as clinical trials that may have hundreds or thousands of samples to process. Now let's switch gears away from the technology and talk about the commerce that's resulted from our GeoMx system. We're still at an early stage in overall GeoMx adoption, but we had a great year. As you can see in this graph, the majority of our revenue today is derived from instruments. Instrument orders have been increasing through commercial adoption. In Q4, we had 25+ orders for new instruments. We now have an installed base of 130 systems, up from just 100 at the end of Q3. Most importantly perhaps, the consumable revenue from GeoMx is starting to be material at $2.8 million in Q4, a 100% sequential increase over Q3. Finally, 2020 was a great year for peer-reviewed papers on the GeoMx system. We're now at about 35 papers, and this is the kind of advertising that we simply can't buy. Increasingly, researchers can go read these papers, get excited about the capabilities of our technology, and then begin their adoption process. As the next slide highlights, perhaps the number one catalyst for us in 2020 that sets the stage for a great 2021, was the introduction of the NGS readout capability for GeoMx. Remember, when we began selling GeoMx, it was only into our nCounter install base, which today is 950 instruments strong. As we open up to read out our Illumina sequencers, we're selling it into a market opportunity 17 times larger than the 950 nCounter systems. Virtually any lab, anywhere in the world, has access to Illumina sequencing, making it possible for them to enter spatial biology with the purchase of just one GeoMx system. You can see this in the steady growth of GeoMx orders and the shift in mix of GeoMx orders towards NGS readout that's shown on the next slide. We finished the year right in line with our pre-COVID-19 guidance at 180+ cumulative orders, an increasing number of which were for NGS readout over the back half of the year. In the fourth quarter, 60% of our orders were for nCounter readout and 40% were for NGS readout. Among those ordered for nCounter bundles, which include the sale of a GeoMx system and an nCounter together to a new customer who didn't have an nCounter before, accounted for 40% of our Q4 sales, a great sign that we're reaching new customers with GeoMx technology. The majority of our GeoMx sales did not require a test drive using our Technology Access Program, and most of the instruments went to academic customers as discovery, enabled by NGS readout, becomes an increasing part of our overall instrument order mix. The next slide focuses on that GeoMx consumable trend and the doubling from Q3 to Q4. We're starting to be very excited about the potential consumable stream coming off our GeoMx systems. In the fourth quarter, 75% of our GeoMx consumable revenue was from repeat orders rather than first-time stocking orders. 60% was for nCounter, but the Cancer Transcriptome Atlas and the NGS readout accounted for an impressive 40% of our overall consumable revenue early in that product launch. Half of our consumables were for protein and half were for RNA, demonstrating the importance of having both those analyte classes. Now let's look ahead to 2021, when the primary catalyst will be the launch of our Whole Transcriptome Atlas, which is now scheduled for the AGBT meeting at the beginning of March. What's really important to understand about the Whole Transcriptome Atlas is it takes NanoString for the first time from moving beyond a targeted set of offerings, primarily focused on cancer researchers and disease biology, to a universal assay that can meet the needs of any researcher, regardless of how esoteric their work is. We'll no longer need to anticipate what targets and biology our customers are in, but rather have a one size fits all offering. This truly opens up, for NanoString, the entirety of the life sciences research market. Look forward to that coming in early March. We're already seeing tremendous early indicators of Whole Transcriptome Atlas demand, as evidenced on the next slide in the mix of our Technology Access Program orders. As a reminder, our Technology Access Program orders are a means of prospective instrument customers test driving GeoMx by sending samples to our labs in Seattle to be processed, to see what the data will look like. It has been a reliable leading indicator of the growth of instrument orders, and what we can see in the second half of this year is a sharp shift towards the NGS readout capability being the preferred modality for people taking GeoMx test drives. 80% of our overall GeoMx test drives in the fourth quarter were NGS, with half of those being on the Whole Transcriptome Atlas and half being on the Cancer Transcriptome Atlas. nCounter readout Technology Access Program is now a minority, as for the most part, customers can purchase GeoMx for nCounter readout without feeling the need for a test drive based on all the peer-reviewed literature we have. As you can see, there was a rapid and compelling response to us adding the Whole Transcriptome Atlas to our TAP program. That is likely to bear fruit in terms of instrument orders in the second half of 2021. Another reason to be incredibly excited about this interest in the Whole Transcriptome Atlas is the substantial consumable value stream, the value of the consumable stream that will be unlocked. As the next slide shows, spatial information is fundamentally more valuable to our customers than non-spatial information. Our typical nCounter customer yields about $250 per sample for one of our most popular panels, which is the PanCancer IO 360 panel. They yield $500 for a spatial equivalent to that, which is our Immune Pathway Panels for GeoMx and nCounter readout. They have been willing to pay $1,250, now five times the average nCounter panel for the Cancer Transcriptome Atlas, and we're announcing today that our Whole Transcriptome Atlas will be priced at $1,750, which we feel is the perfect balance of extracting value for this tremendous information and making it widely affordable and available to customers in the discovery context. Just to refresh, how are we building out our spatial portfolio? On the next slide, we talk about the sequential steps we're taking to address the market. We started with GeoMx DSP plus nCounter in 2019 in the bottom left of this grid. In 2020, in August, we opened up for NGS readout using the Cancer Transcriptome Atlas. In March, we will begin shipping our GeoMx DSP, plus NGS, plus Whole Transcriptome Atlas, and that will really yield for us a full product portfolio in the profiling space, and we think a market-leading one. I'd like to switch gears now and talk about the next step beyond GeoMx DSP, which will be the introduction of our Spatial Molecular Imager in 2022 and beyond. The Spatial Molecular Imager is the equivalent, we like to say, of the Hubble Telescope of spatial biology. It provides an unprecedented amount of detail, when exploring a tissue sample. Here in this particular image, we're looking at 6,000 cells and 600,000 messenger RNA transcripts in just one image. In a normal SMI run, we'd be able to do a great deal more than just this in terms of area. How does the Spatial Molecular Imager complement what we're already offering in GeoMx? As the next slide shows, it reminds you, we believe there's multiple scales at which spatial biology will take place. GeoMx is the market-leading solution with tremendous flexibility in the multicellular scale. Without a doubt, researchers want to map their single-cell biology back to tissue on the single-cell and sub-cellular levels. Really that's where the Spatial Molecular Imager fits in. The Spatial Molecular Imager, as described on the next slide, will provide a single instrument solution for sub-cellular spatial analysis. It will start with standard glass slides that will be stained with in situ hybridization probes, will be loaded onto a single integrated instrument that has fully automated cyclic chemistry and imaging capabilities, and which will report out on an interactive data analysis suite that allows you to explore and interact with the high plex data that is yielded. There are other technologies that are going to be applied over the next several years in the field that we call imaging. Some other companies refer to these as in situ technologies. As you begin to evaluate the different offerings, we really highlight four key metrics that we believe customers will use to evaluate these offerings. The first is the availability to run large panels in terms of the plex, the number of targets. We have already demonstrated 1,000- plex, we intend to increase that number over time. The reason that 1,000- plex is an important threshold to achieve is, at that level, we can build generalized reagents that don't have to be dialed into a specific disease set, but could be applied across large areas of discovery biology. The second specification is sensitivity, so how accurately can a technology detect low copy number of genes or rare events? We believe we are set up to have market-leading sensitivity. The third is the flexibility to analyze both RNA and protein, as both of these biomolecules will be important for discovery and translational research. Finally is resolution, where you have to be able to have sub-cellular resolution, not just in the X and Y axes of the plane of a slide, but in the Z, so you can create 3D resolution for your technology. If you have a moment, and you want to learn more about this, I really would encourage you to watch the webcast replay of our Investor Day, where we illustrated these in more detail than I can review with you this afternoon. Just to hit the highlights, the Spatial Molecular Imager has already achieved 1,000- plex RNA expression on difficult-to-work-with formalin-fixed paraffin-embedded tissue samples. What you're looking at in these images is the highest demonstrated plex in FFPE that any imager developer has shown yet. While we can't show you 1,000- plex dot image, we're giving you an illustration here of some of the more important targets that plexing at that level allowed us to look at. I think, at this level, just to reiterate it, we believe that spatial imagers can be not just applied in translational and clinical research, but also in basic discovery. At 1,000- plex, the spatial imager can simultaneously type cells and map them back in tissue. As the next slide shows, we start with the image, like the Hubble Space Telescope image I showed. Then even without using a classic single-cell gene expression technology, we can develop t-SNE plots based on just the imaging data, and then map each of the cell types therefore identified back to its location and with coordinates in the tissue, and then subsequently allow interaction with data sets in a way that is customary for use of heat maps, et cetera. We believe the 1,000- plex capability, the high sensitivity, and the strong resolution of SMI can allow us to meet the needs of both the translational and the discovery markets. How are we going to commercialize this technology? We're going to start with a Technology Access Program. We're applying the same playbook that worked so well for the GeoMx DSP launch several years ago. We'll be engaging with customers primarily to show the power of the Spatial Molecular Imager to generate data presentations at major meetings and in peer-reviewed papers that show what's possible. Beginning in the first half of 2022, we'll have a beta access program where we place instruments in customer labs, and we'll begin switching our Technology Access Program to more of a test driving orientation, building a funnel of instrument interest that will support our second half of 2022 commercial launch. Look forward to hearing more at major meetings like AGBT about the SMI capabilities, and we'll be reporting on our progress on our TAP efforts through the year. All of what we're doing in spatial biology builds on the strong foundation we established over a decade ago with the nCounter system, which provides a flexible mid-plex gene expression platform that's used primarily in translational research. Just to recap, nCounter is an instrument business that ranges from bench top SPRINTs all the way up to FDA-cleared, diagnostic systems and high throughput, and provides a menu of consumables targeted at the biology of areas like cancer, immunology, and neurology. It's established a loyal following and a great brand for the company over the last decade. As the next slide shows, it's not done growing yet. nCounter is widely adopted in translational research and still placing about 110 new systems per year. Our installed base today is 13% larger than it was a year ago. The cumulative publications are now at 4,000. This is a well-validated workhorse platform in translational research. Each of the instruments continues to generate a healthy consumable pull-through stream. In the fourth quarter, nCounter stabilized after a tough mid-year challenge that came as our research customers closed down their laboratories or substantially curtailed their activity in the face of COVID-19. Instruments were back to what I'd call normal, approximately flat year-on-year compared to the fourth quarter of 2019. Consumable utilization on a per instrument basis was back to about 90% of the normal level. This led to a nice strong recovery in nCounter. While we're not out of the woods yet on COVID-19, I think we can begin to set a goal for next year that nCounter can begin to return to its normalized pre-pandemic growth. That takes me to the three strategic priorities for 2021 that you're going to hear us talk about over and over again. The first is for GeoMx DSP to extend our leadership in spatial with the Whole Transcriptome Atlas opening up the discovery opportunity, and I predict becoming over time, the most important consumable in NanoString's menu. For the Spatial Molecular Imager, we'll be advancing development while at the same time seeding the market with interactions with customers through our Technology Access Program. For nCounter, we're looking for that to return back to a similar pre-pandemic growth profile, similar to what we would have shown in the 2019 time frame. The next several months are going to be exciting, and there's several different opportunities for the investment community to participate in and learn from some customer events that we have oriented. On February 23rd, we'll hold our 3rd Annual Spatial Genomics Virtual Summit, an event where our customers for Genomics will showcase their work, and particularly focusing on the GeoMx Whole Transcriptome Atlas that we'll be launching in just the week following this event. This is open to everyone. The details of it are on our website, or you can contact our investor relations team to get the coordinates. It's a great way to learn about the spatial biology revolution and NanoString's place in it. The following week, the first week of March, NanoString will be at the Advances in Genome Biology and Technology, or AGBT meeting, where we're the gold sponsor this year. We have a record 21 NanoString abstracts accepted for this meeting, most of which highlight GeoMx's capabilities and what our customers are doing with it. We have two oral presentations on the Whole Transcriptome Atlas for GeoMx, and two customer abstracts that are featuring data on the Spatial Molecular Imager. In addition, we'll have a gold sponsorship workshop where we'll be doing our best to pull together this tremendous body of information, and highlight the capabilities and offerings. Stepping back, as we enter 2021, we feel, and I'm going to my last slide here, we feel that NanoString is positioned for spatial biology leadership. We have a tremendous quantification of our TAM at $12 billion plus. We have a product portfolio that's going to cover all aspects of spatial biology. On the nCounter business, we've built a strong commercial channel that's well-aligned to where that market opportunity is. We have a heritage in diagnostics that positions us to capture the spatial diagnostic upside several years from now, and we've renewed a compelling brand and vision focused on mapping the universe of biology. With that, I appreciate your time and interest, and I guess we'll talk to Tycho about questions. All right. Thanks, Brad. We're going to go rapid fire here in the few minutes we have left. First one is just how should we think about the adoption of GeoMx versus maybe other prior instrument cycles, whether it's Chromium, whether it's Illumina sequencers, in the context of you had a COVID impact on 2020 sales, you've got the Illumina partnership, you've got an existing customer base. Is there a good proxy for what the ramp may look like? Yeah, I think the most appropriate proxy for thinking about it is probably the Chromium. Obviously, Chromium was a platform that was priced at a lower price point than GeoMx at the time of its launch. From a unit number perspective, I don't know that we'll keep pace with Chromium, but from a market adoption cycle perspective and the idea of placing a new instrument in front of sequencers, and perhaps from a revenue dollar perspective, we are on a trajectory that we think of as Chromium-like. We also do things like benchmark our overall peer-reviewed publication rates, the productivity of our customers, and major milestones like the method of the year type of catalyst as very similar to what the single-cell biology revolution looked like. Can spatial cannibalize single-cell in the long run? Maybe in the very long run. I think in the next several years, dissociated single-cell analysis that is non-spatial will be used alongside spatial analysis. Dissociated single cell, being able to process large numbers of cells at once, is a great discovery platform and a great way to find new cell types, and then people can naturally map those back to tissue. In the very long run, as the imaging technologies become widely available and highly capable, perhaps there is some cannibalization, but I think of these as largely complementary for the next several years. Illumina recently cut pricing on consumables, $600 genome. Do those dollars now flow back to you, do you think, the incremental savings? I certainly think they will. If you think about the evolution of bulk genomics being the traditional workhorse, but incrementally giving way to single cell and spatial in the same way we showed early in the presentation, I do think dollars will flow from one to the other. Now, the good news is we're making use of all of those sequencers as the primary readout capability for GeoMx. It's not as if the dollars go away or massive redeployment of capital is needed. It's really taking all that great sequencing capacity and deploying it for new types of insights. On whole transcriptome, you highlighted a number of areas, neurology, immunology, cardiovascular, infectious, developmental. Do you think there's a killer kind of app that emerges early on, and what does it do to overall average pull-through? I know you talked about the $1,750 pricing. What does it do to pull-through on average as you roll that out? Yeah, I think it's hard to know what the killer application will be. We're, of course, building on a core history of the company that's been focused on disease biology. If you want to do cancer, we have a great assay for you in the Cancer Transcriptome Atlas. Today, if you want to do neurology or any other disease area, neurology is a very popular one for spatial biology, the Whole Transcriptome Atlas is a more appropriate panel because we don't yet know exactly what genes matter in the field of neurology. I'd say neurology and developmental biology are probably two to watch to start with. I think there is upside, and we've said this many times, there is upside to our previously communicated pull-through guidance on GeoMx. When we launched GeoMx, we described a $70,000-$75,000 per system per year pull-through target. That really was with the translational researcher and the nCounter readout in mind. In the third quarter, our actual pull-through was more like $84,000, and the fourth quarter was $110,000. I'm not ready to declare that that's the new normal, but it certainly is encouraging, and as we move up the price point and we move up the throughput that NGS capabilities and readout capabilities bring, we'll provide periodic updates on what we think is possible. Last one before we wrap up. You talked about 40% bundled customers, nCounter and GeoMx. It's interesting. Who are the incremental customers that didn't have nCounter before that are now ordering both together? Is there kind of a profile there? As well as we've done with nCounter, we're still not fully penetrated in the translational research market. If you think of the 5,000 core labs out there, many of doing translational research, fewer than 1,000 have nCounters. If we find a customer who really wants to focus on the protein assays, which today are most easily performed on nCounter, and don't have an nCounter, then that's the kind of group. Think of smaller biopharma companies, certain academic medical centers that were late adopters of nCounter, or people who had nCounters already but feel they need more capacity in order to support the GeoMx system. That's where we're seeing the bundles. Great. Well, we're going to leave it at that. I appreciate you taking the time. It was a great overview, and we'll talk to you soon. Thanks, Tycho. I appreciate it, everyone.