Wrigley Ganaway. Wrigley is a recent graduate from Brigham Young University, Idaho, in the field of web design and development, with an emphasis in design and a personal interest in multimedia design and marketing. She is from Huntington Beach, California, but currently residing in Salt Lake City, Utah, interning for need someone to blog. Wrigley Ganaway. Hello everybody. I'm so happy to be here today. I do want to preface my talk just by saying all of this information in my talk can be found on the internet. Yes, I learned some in school, but it's all on the internet. Super easy to learn. I'm just a vessel of information for you all. So let's get started. Let's see. So my talk is called Content Creation and Synergy. Planning ahead is the only way to cultivate your brand. So let me tell you how you do that. So when I was 13, I made a Facebook and I posted pictures like that. They were edited on Pick Monkey, I believe it was called. It was just casual day with friends and then when I was 14 or 15, I got an Instagram and that was my first Instagram caption. Got an Instagram. So I've learned a lot since then and I'm happy to show you what I've learned. Let's see. So there we go. All right. Consistency is key. So I want to tell you all today about how succeeding in the tumultuous world of social media is all started by rooting in a young audience and by being consistent. If you're not consistent, your audience won't know what to expect and they just won't have the energy to follow you. All right. Let's see. So first off, I want to start with a brain teaser. I read a study recently and it talked about how, why meme culture, does everyone familiar with the phrase meme culture? Okay, perfect. So meme culture, why is meme culture so prevalent today? Why is this a weird random sense of humor?  Does anyone have any theories or guesses? Anybody? Yeah, that's part of it. When we get to the end of my talk, we're going to find out what the study hypothesized and found. So we'll get to that soon. All right. Oh, there we go. All right. So how many of you have a Facebook? How many of you have an Instagram? Twitter? LinkedIn? Pinterest? Pretty much everybody has all of these five main social media channels. What I found is that people respond better to visual forms of social media because we are a visual society, you know. People use visuals even when they are putting captions on other visuals. They use little emojis. They use little graphics. And we found a way to even make little tiny videos that take one or two seconds, the GIFs or GIF, whichever way you pronounce it. So even the cavemen drew on walls, even the Egyptians drew on walls. People have been using visual aids since forever. It's no secret. Even in Facebook's early days, modern cavemen drew on walls, Facebook walls. And then, yeah, so visual media is the key to reaching your relevant audience. Hold on. Sorry. Trying to figure out my no cards. Perfect. Okay. So visual media is the key to reaching your relevant audience. You need to be, oh, I lost my place. Hold on one second, you guys. Sorry. Perfect. Yeah. You can't just use your social media and your visual media as an accessory to the content that you already have on your website. You need to be able to use each social media channel right and use it effectively or else it will just be something that you have, you know. You need to put it in accordance with your website and your other branding and it will work out best for you. So what do I need? Let me tell you. You need Facebook. So Facebook is a vital tool in social media marketing because it, everyone has it. Everyone has a Facebook. Even if they just use it to connect with high school frenemies, you know, everyone has a Facebook. You can use it to, oh, well, here's the problem with Facebook. So Facebook has some controversy with hacking risks. There's cluttered news feeds. People, like I said, they use it to keep track of their friends mostly. But it's really important to have your business on Facebook. So Facebook is a vital tool in social media marketing. It helps you promote your outside circle and it helps you make local contacts with Facebook ads, with ads manager. And it keeps your business looking professional. So what you want to do when you, with your Facebook is have a good bio. So have a strong mission statement set up on your Facebook. You want to outsource some good reviews from people who have used your services or just clients in general that have good things to say. You want to write post-men for advertising so that you can use them on ads manager, which is a really cool tool. I've used it before myself. And it just works really well for promoting your business and helping you get more contacts. Instagram is also one you need. So Instagram has revolutionized the way we communicate on social media. And let me tell you how. So it's diversified beauty standards with body positivity.  It has sparked new social trends. How many of you take a picture of your food every time you go out? That didn't used to be a thing. It would have taken, I think, I don't know how long old cameras used to take, but it would have taken a long, longer time. It's created a new type of brand strategy. So people share, they do spotlights, comments and likes are worth a lot. It's created a new type of, oh, I already said that, okay, mobilized. It's mobilized activism. If you have, it's caused a chain effect. How many of you had kids doing the ALS challenge where you poured the water on your head? All kinds of things. Let's see. So and it's also created the influencer. How many of you follow influencers on Instagram? I follow a lot for sure. And it has, let's see. Perfect. Yeah. It's created the influencer and the influencer has kind of turned into a job. It has turned into a job. Social media, Instagram has turned into a type of currency where you can, companies will send you on traveling on trips on, they will pay you to promote their brand on your social media channels. Sharing likes, comments, they're all a form of quantitative currency nowadays. Social media is a new type of currency. There you go. All right. So on Instagram, how you want to be successful, you want to share your content on Instagram stories so that people can get real time access into the behind the scenes of your brand. You want to post at least one to two times a day so that people will see that you're consistent and that you have goals and are moving your business forward or your brand forward. You don't want to post too much because it's really easy to follow someone, but it's, well, it's, how do I explain this? It's really easy to follow someone, but it's just as easy to unfollow someone.  Because we don't have the patience to be scrolling for days, you know? All right. And you want to have a theme because we are, as we establish a visual society. So we want, when people go to your profile or your page, they want to see consistency in your theme. They want to see colors that match. They want to see good photography, good layouts, and they want to see good infographics. All right. Twitter. So Twitter has 310 million users and 100 million of those are daily active views, which is crazy to me. Not that crazy because I often use Twitter daily as well. So, yep. Twitter is a semi-professional social network. You will find corporate professionals from various industries as well as people who are just there for entertainment. So social marketing professionals from my industry could market their products on Twitter. Also with their word limit, Twitter allows its users to be exposed to clean and crisp ads from advertisers without populating the feed. This is just a testimonial I found on the internet that somebody was sharing their thoughts about why they use Twitter and I thought it was really relevant to what I'm talking about today. So just reiterate, the word restrictions highlight the important part of the message. So that works to your favor. It might not seem like it sometimes when you need to get information out there. But Twitter is kind of like an RSS feed where you just like scroll and you get the daily news. You see what your friends are up to. You see what Jen Miller and need someone to blog is doing. It's just a quick social media, but it's very important to have so that because everyone is on Twitter, everyone. Hashtags are also very important because you can search using your hashtags. You can do that with most social medias. But Twitter, their hashtag algorithm is actually, I find it superior to other social marketing industries because it helps organize everything. So if you have, let's see, if you're doing a marketing campaign, you want to put a hashtag so that people, when they search that hashtag, they'll just get all of the information on the search results. So and it's also easy to reach out to people and brands that has a immediate sort of interaction capability that Instagram and Facebook don't even have. You know, you have likes, retweets.  Let's see. And the outliers that I have are Instagram and Pinterest. The only reason why I call these the outliers is because I don't use them as often for social media marketing, but they are very, very valuable. And I need to start practicing what I preach, basically. Um, so LinkedIn, LinkedIn is really valuable because it's very, it's, it's a professional environment. People don't use it for scrolling.  What you want to do with LinkedIn is have two profiles, one for you and one for your company or your brand, because it just separates it and it makes you more marketable and more, what's the word I'm looking for more?  So you can do that by just making a personal page and company page. You want to have a specific advertising or marketing goal so that people know what you're about when they go to your page.  They want to see why you're on LinkedIn and what you have to share with them. LinkedIn is special because you can optimize your company page. So you can optimize within LinkedIn so that your pages come up for other peoples. And it's all in the back end, it's very easy to do. Visual content, it supports visual content, of course, all social media channels support visual content that I'm talking about today. But you want to put the visual content first and forward so that you can grab your audience's attention and give them what they're looking for. And ads, you can also monetize slash optimize ads on Facebook because, sorry, on LinkedIn. And that helps a lot because that also helps with your SEO with your company page and your personal page. All right, now Pinterest. Pinterest, I love Pinterest. Does anybody else love Pinterest so much? I scroll Pinterest for days, mostly personal use, but you know, it's still important to marketing and social media. So I found this really cool quote on the internet, photos are center stage and sharing is second nature on Pinterest. When you go through, it's all right there, you literally just have to tap and you have five options. It takes three clicks really. So Pinterest highlights the trends, which is really important. It gives like a one stop shop look into what people are looking for, what is popular in audiences today. And we see this in Target and Nordstrom, if you've ever been to Target or Nordstrom, they have little tags that they put on items that have been doing well on Pinterest. So they're used in a real world way to promote the company's social media, which is something you could do as well. Lowe's uses it to show products in action. So they use the storytelling principle. They use, let's see, they take a bench and they do a project with it and then they post the project on Pinterest and they get people to follow along with that. And that is just another way to get people to see what you can do and follow your branding. Let's see, if you were a paper company, let's see, how would you personalize your product? You would put on Pinterest, let's see, this is how you make an origami rabbit. This is how you make a little cutout to put on your wall. This is, you can make homemade cards. You know, it's using it in a real world example humanizes your brand and makes it more easy to relate to. And there is a unique opportunity on Pinterest to humanize your branding, like I said. How do I keep track of all of these social media channels? It's very difficult. There's a lot and it requires a lot of time. You don't want to use too many. You'll get burnt out. You'll spend revenue and time on social media channels that don't apply to you. So what you want to do is either hire a social media manager or be a social CEO. So as we approach business more casually and more transparently, it's becoming more and more prevalent in business to be a social CEO or be in control of your own social media. It humanizes your branding, which is something I obviously love to talk about. I keep saying it. And it makes you more relatable on your social media channels. So take Elon Musk, for example, he is the CEO of Tesla, I believe. And these are some of his tweets just highlighting, you know, Tesla, they got 100% crash rating. They have it available for renting, you know, he's just promoting his branding right now. But oh, there we go.  And he's gone from in 2011, they made zero cars and fire in 2019, they made 500,000. So that is some pretty intense growth. Yep. So Tesla and Elon Musk, he's a good social CEO to look up to. He's not the most perfect example, just because he does have a separate Tesla Twitter and his own personal Twitter. But he is a great example of a social CEO. People know him, they know his brand, they know him together. Let's see. So cohesive, how do I make all of my branding cohesive? Tesla, for Elon Musk and Tesla, they use a mix of meme culture of science and just randomness. But you want to find your theme, your voice and your posting schedule.  That's why it's important to have one social media person because it makes it easier to make a voice to it sounds like it's all coming from the same person. And the posting schedule, it's important to stay consistent in that because your audience expects something and if you don't have anything to deliver, then it won't work out as well. Let's see. So let's talk about posting schedules and content calendars. Social media and website content need to work together to keep you accountable to your social, to your branding and your marketing. It's easier to engage, it's easier to reach your clients and your co workers, your just peers in general. You want to keep web content and socials working together so that they benefit you the most. So your social media is going to engage larger audiences. It's going to give you an online persona, which is very important today, and it's going to give you active marketing results. If you have a business Instagram, you can literally look at your insights right away right after you post something you can see what percentage of them is male or female, you can see what age groups they are. It's really cool. And website content is going to provide the meat of your brand, it's going to direct people to your site and tell you and tell them what you do.  And it helps with SEO, which is search engine optimization, I'm sure you know that. But so social media actually helps with SEO as well, but website content by nesting and Google and everything or nesting and Google. It helps a lot. Bring your information up on the search engines. So here are some content calendar tips as well, because we want the social media, we want the website content, but we have to keep it consistent. And that takes planning. You want to have a rough outline of posts, photos and articles or written pieces thought out and ready to go one to three months in advance. I find I mean, I find it's different for everybody.  So you want to use an online calendar or planning service like Google Suite or some WordPress content planning tools if you use a WordPress site. So here are some that I found. I have used Trello. I haven't used co-schedule or published press, but they look amazing and people really like them. So Trello is free and it has different boards to outline the tasks. The plugin displays everything and it organizes everything into whatever categories that you put them into. It is just a great plugin, which is something you want if you have a WordPress site. Everything is on the front end with Trello. So it's a little bit of a learning curve, but it's pretty easy to use once you get there. So with co-schedule, it's great for social content specifically. It's better for established earning sites simply because it is costly and there is quite a lot you can do with it. So you want to be able to fill out all of the areas of co-schedule if you're going to use them. It has automated social media, so it's perfect for the social content. And published press is free. It gives you full control and a great UI experience, user interface. There we go. And it's just back in control, very easy to use, great user experience. And you can add people onto projects, which is something really valuable if you're using it for a web building business or a business that's larger and has a lot of employees. The free plugin offers enough for any social marketing person. But you can pay to integrate other plugins like WooCommerce and things like that. All right. Another tip is to use an app like Preview. That's just the one I personally use, but you can watch your brand theme. Preview is used specifically for Instagram. It just lays out your Instagram and you can write your captions and schedule when you're going to post it. I find it really useful to use because you want original content and you just want it to be cohesive and nice. You want to have blog posts ready to publish and link in corresponding social media posts. So you don't want to just put a post out about your lunch and then say, oh, look at this website article I did on how social media marketing is great in the world today. You want to be able to have them be relevant to what you're posting or people will just be like, she's fishing for whatever. It helps with search engine optimization and website engagement as well because people can click on these links and go directly to your website. I was having a conversation with someone yesterday about this, though. And one thing you don't want to do, one thing that I don't like personally is the link in bio business because that changes so often. You want to find a way to include your link in your post so that people don't have to go to your profile to click on your link. You want to use relevant and proven hashtags. I say proven. It's just if you search it, it has a lot of hits and it is used a lot. So people are searching it. People are using this hashtag and trying to see what people post with it. And you want to plan with original content. So when you're planning, if you're doing one to three months in advance, you want to be able to have all of those visuals ready before you put them on your plan. You want to make sure that you don't want to get to the day of and be like, oh, no, we have this post that we're going to do and we don't have the visuals for it. That's never a good idea. It's how can you set yourself apart with your visual content? You want to know when to post as well, but you can't take it too seriously. It doesn't matter too much, but it is good to know if you are looking to get the most accurate marketing feedback from Instagram, from Twitter, from Facebook. So the best posting times are Facebook 9am. Let's see. Let's see. Yeah, let's see. So Facebook is 9am. So Facebook is super popular in the industry, business, you know, so lunch, morning commute, three to 4pm. They're great to post then because people are scrolling through their Facebook when they should be working. And it's the best time to post on Facebook is Thursday through Sunday. Instagram one to 5pm because that's right in lunch hours and it's right when work is over. Instagram is a little, it's a little more browsable than Facebook, but Facebook is sometimes more interesting to people to browse during the day. Twitter is like an RSS feed, like I said, and so it's easy to scroll. So a lot of people are scrolling while they're driving 8 to 10am and 6 to 9pm during morning traffic, during night traffic, just the commuting hours. Days to post on Twitter depend on your business and what you're selling. If you're selling something like photography services that you would probably want to post on the weekend so that people could see it, but really posting on posting days on Twitter don't matter as much. LinkedIn 25% of adults use LinkedIn during work hours, which makes sense because it's more of a professional sort of social media channel. But it said here in my research that 10 to 12pm is when LinkedIn gets the most like scrolling. So it is beneficial to know that just so if you're doing interactions on LinkedIn, you know when you're going to get the most out of it. And Wednesday is the best day to post on LinkedIn and Pinterest is heavily female. It's 29% active users, which is great for a social media channel. And it's a little less browsable so people don't really view it until 8 to 11pm when you know moms who are doing DIY projects are going to bed or putting the kids to bed. So let's see. So that's when you should post. How do you make it work for you? How do you make your social media work for you? Where does your brand succeed? Look at where you succeed. Look at your target audience and make a persona, make a schedule. You know, that's what planning is. It's making your life work for you. So you want to look at your social media as a priority and make sure that it works for you and it's not just something you're checking off a to do list. Social media should be fun.  All right. And you want to develop an agreement with your audience. So it's important to know the trends and what audiences are responding to. It will help shape your branding. It will help determine marketing moves and influence your visual representation. So you need to be aware of hot colors. You need to be aware of photography style, editing style. Are you a more jokey company or are you all business? You know, you need to make it personalized to you and help you move forward with your branding. And staying on trend is social media branding gold. You know, it will keep your business booming. It will keep clients coming in. All right. And here's my brain teaser. Okay. So the let's see. Okay. Well, here's the answer to the brain teaser, you guys. So so the reason why meme culture, the random sense of humor, you know, is so prevalent and so popular today is because we have the world at our fingertips, right? In our phones, we have all the visuals, all the words we're just scrolling for days, you know, we've seen every word in the English language, probably since social media came out. So so because we've seen so many words and content in such like compounded amount of time, the only way that our brains are stimulated, and it's not the only way obviously, but pop way that our brains are stimulated stimulated is by content and words that are strung together that don't usually get strung together. So things like the Skittles commercials, you know, that's pretty weird. The old spice commercials, and the Super Bowl commercial with the puppy monkey baby. Did anybody see that a couple of years ago? Super weird. I did not get it, but whatever. So yeah, you just need to be aware of the trends and be able to see what kind of socials people are responding to. And that seems to be the weird randomness right now. So have fun with that. And you want to be consistently on trend, like I said, and that will just help you gain a loyal audience.  And you want to be ahead of the curve with that. So I would start now. Consistent planning and using relevant social media will help you stay ahead of the curve. So you need to be planning, you need to be aware of what your next steps are at all times. And that is it. So these are my, I'm, that's my Twitter, and that's my email. If you want to discuss this more, but thank you so much for coming to my talk, you guys. And that's it. Thank you. Any questions? I will take a selfie, and I'll put out my Instagram stories. Let's see. Okay. Perfect. Yes. If you want to follow the trends. So on Facebook, sharing articles is really important on Facebook. Right now, I'm just pulling this out the top of my head like I said, I found this all from the internet. I'm just a vessel of information. So if anybody has any other feedback, I would be open to hearing it as well. But Facebook, you want to share, you want to have visual media, of course, you want to share pictures, you want to put a very heavy importance on your visuals. So on your pictures, you want to have flat lays are huge right now, flat lays are big. Let's see. You just want to include one of the trends that I've been saying recently is, like I said, the social CEO, you want to include the behind the scenes and you want to you want people to feel connected to your brand in a personal way, essentially. Yeah. Yes. Yeah, definitely. You want to comment and engaged. Anything else? Yeah. Yeah, you're right. Right, right. Right. Let's see. Well, I don't know. Does anyone have a solution to that? Anybody have any ideas, Jen? Because regardless of when your audience is going, they're still going to see that you can consistent. So they know what you expect from you. Yeah, very true. Yeah, exactly what what your target audience is, maybe pick that time zone if that has a time zone. And if not, then just, you know, you don't take it too seriously. The times people will see your posts because a lot Instagram, Facebook, I don't know Pinterest, I think, they're not chronological. So it doesn't matter as much.  For sure. Instagram. Yeah, so Instagram, you want to post one to two times a day, but you want to keep your stories active. So but you don't want to be too active, you know, you want maybe your main posts, which is the most important part, you want one to two times a day, any more than that. And people will be like, Whoa, she's spamming my newsfeed, you know. Oh, of course. Yes, sorry about that. So the stories is what you would. It's like the behind the scenes area. It's in the moment. It's like a live, it's not live, but it's right away. You take the video and you post it right away and people can click on your little profile bubble and see what you're up to at the moment.  You want to make sure that your content is relevant and important to what you're trying to say. Yeah. So going back to consistent posting. What would you define as consistent like posting, making sure to post several times a week or going the extra step of I post every Monday, every Tuesday, skip Wednesday, every third like making a schedule like that. Is there a is there a key to that? Or is it just is or can it be just as loose as I make sure to post three to four times a week sort of thing? Personally, for me, I find when I have like a rigid schedule. If I have it scheduled that day, I'm going to post this Instagram picture, then I will be more likely to do it. So if you want if you want to grow your social media and you're absolutely serious about it, I would I would make it a little more rigid of a schedule than so you would you would pick out actual days that you will make sure you post that week every week. Yeah, and you want to know exactly what you're posting as well.  And I actually saw you at work on this where I need a beach day. Yeah, it's true. It's true. So I when I was using preview, I was showing Jen Miller is my mom if any of you know she works for me. She is the face behind need someone to blog and she has a lot of input into this as well. So I'm happy she's here. But when I was showing her my preview, so I was just using this for my personal Instagram, because I want to be an influencer. I want to be paid to travel to you know, Cabo or whatever. So so I was planning the beach day that I'm going to have tomorrow probably. And I was going on Pinterest finding inspiration for my photos. And I was writing my my comments and my captions in my little bubbles. I don't know what was the question you had like this whole Yeah, well you want. Yeah, that goes along with making a theme for your brand on.  But the theme of your Instagram speaks a lot to people who visit, you know, if they go to your Instagram, they see a theme, they're going to be like, Oh, she's serious about Instagram, you know. So it's just, I don't know, you want to match your editing style, you want to match your layouts and everything like that. Well, if you're selling a product, you can include that. I don't know if it's available to everyone yet, but I think it will be as soon if you have a business account. You can link to that product and people can click on your picture and there'll be a little bag item and they can go there. Or you could just manually put the link in. But no, if in your bio, you could put your website link just a blanket website link. But if you have a specific post that you want to link, I would recommend linking that specifically in your post. Yeah. Yeah, of course. Yeah. Well, there's this girl I follow on Instagram. She's a little more of a she's a in fashion and stuff. And it's just someone I follow out of personal interest. But I think she does a very good job at her Instagram per say, but social media all over the place. Let's see what am I? Hmm. So her Oh, right. Her name is let me look at her name really quick. It is Alyssa in the city.  And I just her she does a really good job at keeping a theme at keeping consistency and keeping up to date on her stories on her bio on everything. Let's see. Anything else? Yeah. No, I haven't. I have or I know people that do they find it easier for them. But I, I don't want too many hash. You don't want too many hashtags on your posts unless they're separated are on Instagram on on Twitter. Instagram are on Twitter. Hashtags are a great thing to use so you can use a hashtag generator. But I find that just thinking of them myself and finding out the ones that work for me is better. Yeah. Hmm. Yeah. Okay. YouTube I was going to go into YouTube. I didn't I didn't go very go into it at all really. But I was going to mention it. I don't know much about how to use YouTube. But I know Twitch is really big right now. Twitch is huge. So if you and it's a little bigger than YouTube, YouTube is kind of faltering on the social media channels right now. But yeah, anything else? Thank you so much, everybody for coming.


So here's the ARM embed reference design smartwatch using a memory LCD and can you show some of it? So there's a smooth UI What is it? What is it? This is running embed. This is running on the OS. Yes. So what can embed OS do? So embed OS is showing the low power features. So and embed OS is for Cortex-M class processes. So which Cortex-M is in here? So we have what we have in here, which is the board which we have inside. This is the first version of the board. We have the second version, but we are still working on it. So the main process, Cortex-M3 from Scylabs, which is the giant gecko. Just that one. All right. So there's a Cortex-M3 in there. Yes, we also have Cortex-M0, which is in the booted chip. Is that one? One Cortex-M3 and one Cortex-M0. Yes, we also have a fingerprint sensor You can see it here. So working on it and it has the co-processor, which is Cortex-M4. So there's also Cortex-M4 there. So there's three Cortex-M inside there. Yes. And what kind of sensors are going on the side? So what we have in terms of radios, we have GPS. We have Bluetooth. We have NFC. We have nine-axis sensor, which is the accelerometer, gyroscope and magnetometer. We have ambient light sensor. We have RGB. We have capacitive sliders. As you can see, the sliders are in here. The capacitive buttons are in here. So as I go through the menu, I'm using the capacitive slider. And then we have the micrometer in here. We have the user cup and the digit in here as well. What is the user cup and the digit? Like, okay. Yes. All right. And can we look at the battery module there? Yeah. So what we're showing in here is the power consumption of the NBAR OS. So at the moment, the watch is basically being a watch. So this is the power consumption right here. So 0.02 milliwatts. What is that? Yeah. So it uses around 70 micramps, 70, 80 micramps. And that's with the actually animations. So every minute, you actually do the animation of changing the minute. So that actually uses quite a bit of power. And even with this and Bluetooth on, the watch is still using around 70 micramps. So the battery lifetime, what we expect for it, the initial assumptions are around two months. Two months, battery life? Yeah. With this Bluetooth 4.1? So it's Bluetooth low energy. Yeah, BTLE. What is this battery capacity? So battery is 160 milliamp hour. Just 160 milliamps? Two months of battery life. Yeah. So why isn't everybody making this yet? Is it only a reference design? It's only a reference design. It depends what you actually want to achieve. So if you would like to have a nice animation and an old color screen, then you do have the application processing to go on. Yeah, but memory LCD also has color. It has color, yeah, but it's not probably as nice and high-end. Let's see some UI a little bit more. Yeah. So basically you can go and there's a heart rate monitor? We don't have a heart rate monitor. Just an UI? Yes, we don't have a heart rate monitor filled in. We had one demo where the heart rate monitor was connected to Bluetooth. So you could wear it. Okay. So it's Bluetooth to some different peripherals. It could be any Bluetooth headphones, headset or something and then Bluetooth to the phone. Right? Yes. That's the main function, is connecting with the phone? Did you already make the Android app for the phone? We have one, yes. I was just trying to connect it. All right. So how do you make this decision? What reference design to make? Who makes that decision? So the decision was made a long time ago and the project has been running for quite some time. Even started before I joined the company. What do you do? So I work on the hardware of the watch. So I actually work on the schematics and the PCB board. That's fun, no? It is fun, yeah. And we have a guy here, Steve, who's working on the mechanics of the watch. You work on the mechanics? So what kind of mechanics are you doing in there? Well, we turned the industrial design into something manufactureral. So my role was taking the design and turning it, taking it into individual parts, getting it all assembleable and putting it together. So how can you do that? Do you have experience in doing that? Yeah, so I have experience in product design. What kind of products you were doing before? I was working in robotics before this. All right. So is Arm going to mass manufacture this? I'm joking. How is this different from a pebble? So the difference really is that we are not manufacturing it. This was an experiment. And it was an experiment to learn about how we develop devices like this to influence our reference design. We wanted to learn how to build low-power systems and how to architect our devices so that they would be low-power. So it looks really good. So what is M-Bed OS? Is it Linux? It's not Linux now. It's not Linux, but it's a firmware or no. It's the operating system for Cortex M-Class. But how much can it do? You can do quite a bit. So in terms of it's an operating system for microcontrollers and one of the main features is security of it as well. So it's pretty tied into M-Class processes. So people can take this and do lots of real things and they can take your... Is it open design or what? Yes, it's an open design. It will be released in the first quarter next year, 2016. So you will release an open smartwatch design that any manufacturer can take and start doing crazy things with. Yes, so we're talking basic wearables here. So M-Class wearables and any manufacturer can take parts of the design, all of the design, reuse it, how they would like to get started building devices with M-Bed OS. So it's got to be fun to make designs for hardware that can be mass manufactured and open and get acceleration into the industry so people will use memory LCD. How about e-ink? Is there a consideration about e-ink also? It can work too, potentially. So it could be different displays, people can change stuff, module are a little bit or... And the software would be improved for this because it's not the same M-Bed as the other M-Beds, no? Or is it the same M-Bed? It's the M-Bed OS. It's just the same. So there might be subsets of M-Bed OS. There might be smaller, some of the features might be cut off. So for example, on the watch, we have... On the main processor, we are running M-Bed OS, but we are also running M-Bed OS on the Bluetooth chip, but it's just a subset of M-Bed OS. So there's a different M-Bed OS on the Bluetooth chip than M-Bed OS? Yes. So with M-Bed OS, you're supposed to pick what features you'd like to use. And if you don't want to use something, then it won't be compiled in. Nice. But if you want to do a smartwatch that has more and more stuff, then you would take M-Bed OS and just increase the size of it? So in terms of this difference design, what we have, we have a big subset of features. We have various radios. We have various sensors. And if you'd like to pick it up and build it your own, you're free to do it once it's open source. And in actual design of the watch, if you wouldn't like to use, so you can still make the same exact watch. But if you don't want to use just some of the subset of the features, let's say you want to use the main processor and the BLE, then you just use these two. And everything else, because it's on a separate sort of subsystem, you can just power gate here and you won't be using much power. It's just a leakage. So let's look at the watch again. So what if somebody wants to do a more advanced user interface and have more stuff? How would they do it? So in terms of more advanced user interface, yes, you are free to do it as long as you do it yourself. How does it work? Is it like you install some kind of home replacement that they have on Android? Or how does it work to do more UI stuff? So in terms of more UI, you probably would have to... Honestly, I have no idea if you can have your own libraries for it. Probably you would. And then that increases the memory space on the device. Oh yeah, of course. So as long as you take it into your own hands, you would use a subset of NBDS, and then you start adding your own stuff to it. So then it depends on you how you do your own programming. What do you do when you click on battery? What does it do? So the battery, what it has, it has a fuel gauge inside. You have eight weeks battery life left. Awesome. It's not constantly on Bluetooth connection, right? It mostly is. So not this one. This one is mostly on Bluetooth connection. And what do you do with the version 2? You say there's a version 2. So in version 2 we have some of the components have changed. The NFC has changed. The sensor has been upgraded from six-axis to nine-axis. Bluetooth is still the same. The co-processor of the fingerprint sensor has been moved from the main board onto the smaller board of the fingerprint sensor. So smaller tweaks.  No, no, no. It's still the same. It's still the same. Not more power consumption? No, no, no. Not less, not more. The only thing is additional features. We've added quite a few power gates. Is it possibly potentially cheaper to manufacture the next version because it's more optimal? Not really. No, no, no. It's still the same board. So we actually have an eight-layer board in here, which is rigid flex. It's still manufacturing process. What's potentially the price to manufacture this? We haven't looked into that yet. You haven't looked into that? No. You can ask, of course you can ask. Yes. Hey, can I ask you one thing? What's the mass manufacture price you think for mass production of this one? It's difficult to calculate that because it depends on the volume of the device and we're not building large volumes. If somebody's making a million units. Of these exact devices? Yeah, yeah, yeah. It would change significantly if you're building a million and I don't know how much it would cost. Less than 50? I have no idea. Okay. At the moment we're doing PCBs in the UK, it's a bit more expensive. As soon as you want it to do more, you'll probably outsource it somewhere else. But the ARM Cortex M3 and the M0 and the M4, that's not very expensive. Oh yeah. It's possible to get them for... Yeah, it's cheap. The only thing at the moment is PCB manufacture is expensive because it's a... Custom, it's special. Yeah, yeah, of course. The display is hopefully not too much and there's capacitive touch on the side. That's just a PCB. That's actually just a flexible PCB. Flexible? Yes. Let's see it again. What do you mean flexible? So the PCB inside is... Yeah. So the PCB... So the PCB... This is where the LCD connects. Yeah. And that's where the... Another PCB connects. This is where the flexible PCB connects. Okay. Sorry, one second. I just get to cook it. Okay, right here. So you say the PCB connects? The PCB connects in here. And what it is actually is a flexible PCB that goes around in here and in here. So what I will do is we have four capacitive buttons which we use as a slider. And we have another three capacitive buttons here that I'm going to use in the middle one as a back button. So it's flexible? That means it goes in the shape of your wrist a little bit? It goes in the shape... So it goes underneath the glass panel that's in here? Wow. Okay, but it doesn't shape with your wrist or something? No, no, no. But it's just like this. Yeah, it's mounted in place. And it's not going to break? It's not going to break. But you're not wearing it every day right now? We're not wearing it every day. It's a little bit fragile. Of course, yes. There's not many. With every design you see some flaws with manufacturing. So let's say with straps they might be getting dirty a bit. But to take this in mass production then people need to test everything a lot. Of course, if you're taking to mass production then there will be a bit more quality testing as well. All right, cool. So that's awesome. Reference designs for smartwatch. Give me a question. It's arm and bed, too. Yeah.


So, are we ready to start? Like coaching under six soccer, are you ready? Okay, so everything here is screen comic licensed. I think Michelle probably went through that. It's totally open. We still need to reuse that fusion. This is, you know, we try to publish open access and so on. All right, okay. Module one, introduction. So this is going to be less of a technical sort of introduction to meta genomics. As much as sort of a conceptual overview, we're going to talk about some detailed things and certain types of experiments. But my objective is to really get to thinking about meta genomics and then sort of starting off interacting with some of the resources. My tutorial, by the way, is on the wiki now. And as you'll see, it's really about trying to interact with the data, finding different ways to joint the data down from the online resources so that you can get started with other people's data should you have the courage to do so. I want to acknowledge a couple of really key contributors. So the first of course is the Canadian bioinformatics workshop as represented by Michelle, but also has sort of run and tremendously supported by Francis Lillet. If you haven't met him, you totally should. He's a really, really fantastic guy. And Michelle and Francis have been extraordinarily busy over the last two months because this is the 10th this year, Michelle. 11, okay. And so now we have the Center for Comparative Genomics and Evolutionary Bioinformatics. This is a range of researchers who work on sort of theoretical aspects, mathematical phylogenetics, applied metagenomics, a lot of protostology, really exciting creatures and listening to the taxonomy for 15 years, I still haven't learned it. Dino Atlantic is our local Dino Center that tries to facilitate connections and try to bring basically more research funding to researchers in the region. And oh, there, that's me. So these are my contact details, our VCO at LCA and we're on Twitter. All right, please, please make the most of your visit. And I'm, like I said, we're happy that they help facilitate anything that you want to know about the region, anywhere you want to go. I know some of you are taking the opportunity to camping or something I wanted to mention about Halifax before I finally shut up about Halifax is that there's a very important person who was born in Halifax, not as Oswald's baby. Right, and so some of you may be familiar with this experiment. It was not that, you know, everybody's like, oh, Watson and Craig, discovery of double stranded DNA. I mean, that's fine, right? Okay, that's great. But the, so some of you have probably learned this in like first or second year university and I don't want to dwell too much on it, but it's not. The smooth strain, which is non-burialant cannot make my sick or dead. You've got the smooth strain which is burial.  So you heat them up to some sort of temperature where they can no longer survive. They go, hey, and then you would reduce them into the months. Do you want to change the color scheme? I have no idea. I've not seen this window ever before. Yeah, let's try to do that. Right on, okay. So is that 10 minutes and we have our first room? All right, so. Bye-bye-bye, nucleic acid. So rough strain plus DNA from the smooth strain equals bad rough strain, equals dead months. So also changing the world, right? So we have six modules. The first one is delivered by me, Juan, and basically talking about what we're talking about and different approaches sort of at a high level. And then we're going to investigate things in more depth. So Will Sows at the back. I hope you got introduced to Will. You'll get interested. Okay, great. I'm just going to be talking about certain protein-based approaches in particular, the 16S ribosomal RNA gene, right? And then tomorrow is Mediginoma Fest. So Morgan Langell is going to start in the morning with taxonomy and the afternoon with functions. I feel like we're going to end with that in a minute. Module five and six, John Parkinson from the U of T, who's done a lot of methods to develop more of the metronomex. He's going to be talking about the field and some of the crucial tools, and then a bit of a work through on some of that analysis. We're going to finish off the icing on the cake. It's going to be a good afternoon. This is a lecture that is going to be delivered by John Parkinson with a tremendous amount of input from Keona Brinkman from Simon Fraser University, who I'm sure some of you know, who contributed a great deal to the development of this workshop, but could not make it due to other travel commitments. So we're very disappointed that she can't make it, but we'll give you the spirit and the PowerPoint slides. Before we want to introduce you. I want to probably speed things a little bit. So the basic idea is, what is the objective of your process, right? How do you deal with your own data files? What are the standard pipelines and how do you run them? What do you do for the analysis? And then of course, the crucial one, also known as the crucial or critical one, is to recognize the technical limitations of medicinal studies, right? Because if you spend $60,000 on Pac-Mio sequencing in the U of T metagenome, you're like, wow, we've discovered the key to... I was hoping for something more irrelevant. We discovered the cure for malay, right? And then you submit it for review and they're like, this is the stupidest thing ever. You should use aluminum instead of Pac-Mio. Ah, okay, and then you get a scoop. So these are very important considerations, not all at the detailed analysis command from GUI level, right? So I sort of want to think about this at a few different levels. Sure, for my maximum. We're gonna start by talking about some terminology, semantics, just because this is a discussion that comes up every time you talk about metagenomics. So I just want to kind of make sure we're all on the same page as to what it is we're talking about. As a metagenomic experiment, what's the appropriate choice of technology? Interpreting the contents of sequence files. So this is mainly, I mean, fast A is like the simplest format ever. We're gonna take a little bit of a look at the fast view format, but I'm sure many of you are familiar with any way during the tutorial. And then Will is going to, I think, hitch a full on with the files and the processing and the Python and the whatever else he's got at the door. And then the one that we're gonna focus on is what are the online resources and what are the different modes of access you can get in order to bring these data closer to us. And if you read that really quickly, don't put your hand up. Who wants to hazard a guess as to what it's metagenomics? Come on, you're not all jet lags, okay? Right, Christine, coffee. That's great. And I think that is the closest to the original Lederberg definition from your announcement, right? We're gonna actually reset that. Personal communication. So the collective genome of our indigenous mother, the set, and that you think that comprehensive genetic you are almost thinking that in life form should include the genes in our microbiome, right? Another way of looking at it is that it's somewhat equivalent to the organisms found in a particular setting, right? So hopefully you see the difference. In one case, it's all about the genes. In the other case, it's all about the things that contain the genes, right? And so either of these definitions is okay. I'll tell you right now that I tend to use this one about the microbes and encompasses all of their genetic stuff and metabolomic things that are going on in the meta genome. So that's the microbiome. The meta genome is a term that's tossed around all the time and the press and the adipose shock. This is Joe Nicholson, 1998, right? Advances in molecular biology and new periodic genomics which have laid the groundwork for cloning and functional analysis of the collective genome of soil microflora which we turn the meta genome of the soil. Now there's one really important thing about this and actually Pat Schloss tweeted this a couple of weeks ago. Where does it say sequencing it? Does it, right? This is about cloning and functional analysis, right? So it's using the genetic material but it's not necessarily sequencing it. And if you look at some of the first papers such as Joe Handelsman looking at AMR, anti-microbial resistance genes and say Alaska, it's not about sequencing. It's about let's blow up the environment of microbes that is and clone random bits of DNA into like plasmids and then express and see what we can find. No DNA sequencing required at all. So the purpose of these sort of tedious introductions is just to try and make sure we know what we're talking about and make sure that we have sort of the right broad perspective on these things. Because you know, you say these terms that, oh, by the way, it's not encompassed marker gene survey that was published a few years ago in the new science of meta genomics. Revealing the secrets of our microbial planet and a National Research Council of the time. Yeah, Claire Fraser, Jeff Gordon, Ford Doolittle and a number of others as well said that it did. So marker genes strictly speaking according to the definition not really because if you do cloning of 16S and then do expression tests, that's kind of boring. So it's ambiguous, right? But let's just combine that with the point, right? Well, I tried to come up with the simplest definition of why we do this stuff. Let's explore the relationship between microbes and their habitat. That's a fair definition. And then how do we accomplish this? Well, this is where the rubber hits the road in terms of, you know, experimental design, bioinformatics, statistics, hand waving and all that. And there are many, many, many, many different ways to profile the community, right? Here are six. And actually, here's something that we can do. So there are six. And then maybe we should have a look at what you're doing about to indicate whether or not you have done this type of analysis. I think this would be a very interesting survey. So marker genes, okay? Over half the room. Metagenomes, right? So this is the environmental shotgun type stuff. About a third of you. Metatranscriptomes, now we can count, right? One, two, three, four, okay? Metaproteomes. And, okay, zero. Metametabilomes. We're gonna be doing some of this in a couple of months. Excellent. Contraromes. What is a cultureome? Yeah, so cultureomics is a term specifically designed to make Jonathan eyes very angry with you. But the objective is to try and actually grow as many things as you can from a given sample. Why would you wanna do that? Because, hey, it's a mess in there. To the extent that we can tease certain organisms out, we might be better able to characterize their biochemistry. Three, grow them in more tight combinations with other organisms. And I have a beautiful example of that later on. It's not specifically cultureomic, but it kind of takes you to part of the reason for cultureomics. So, most of the great things that have to nominate should be capitalized. And the claim that has been made for decades, including sort of in this seminal paper about the gene analysis of Monaco 1995, is that fewer than 1% less than 1% across many habitats are cultural, right?  And the things you get to grow are born, right?  Whereas, you know, Mexicaucasanthus, candidata, syringes, cellulose, whatever, those are like the exciting things and they won't grow because they have very specific requirements that you do not know about, right? And so if that's the case, then if you just do culture, you get a very positive. And even if 50 or 70 or 80% was cultural, I mean, there's still two problems, right? One is that you still have 20% that you can't get at through these traditional methods. The other is that if we're talking about the human microbiome, whatever that means, then you're culturing 500 things, right? That's a lot of very hard-working graduate students, right? So it's, you know, now we have met it in a way, sort of this sort of environmental shotgun approach, or indeed, if we use a broader definition of the morphogen approach, then we get this broader picture of, and to use the sort of cliche, who is there and what are they doing? The definition of the microbiome was actually quite specific to humans, but it's generally accepted, at least among people that I talk to, that this is a term that is relevant to any sort of habitat, any sort of biome on earth, right? So when I say microbiome, I'm not just talking about humans, I'm talking about, you know, soil, ocean, rivers, talking about hydrothermal vents, talking about wastewater ponds where graduate students get to carry shotguns to scare away the cold, the polar bears, all of these things, right? And so the scale of the human microbiome on a civil host, if you were to see it right, how many genes do humans have? Well, somewhere between 20,000 and 25,000, this is about 25,000 plus or minus 50,000. Now, your typical human gut microbiome sample will have on the order of greater than 160 species. It can be several hundred species in scared boats because we lack a good definition of species. And, you know, over a million different genes. So in terms of functional diversity, of course humans have all these confusing things like introns and shuffling and routines and whatever that makes me glad I don't work with them. So there is more complexity than that number 25,000 would imply, but I mean, this is significant, this is substantial, right? It's true of any biome on earth. I want to kind of get at the roots of metagenomics, just because I think it's important to kind of take a look back and see where the field has come from and some of the techniques that have emerged over time. So I won't do that yet, we'll get to that. Okay, let's start with the 1970s, which I would actually be talking about because one Nobel Prize is not enough. He got his first Nobel Prize for sequencing the protein sequence of insulin, right? 1960 was actually the first to be in a sequencing method. It was not very useful. I mean, it was amazing at the time, right? But it doesn't give you everything. It's what it was. So isn't it interesting? Because those of you who know about, you know, very simple, homo-period or homo-magnetic sequence, they were actually the only things that people could see, the sequence 45 years ago, 55 years ago. And of course, if you don't know whether Margaret Bacoff should, she was a pioneer in many ways. She's been referred to as the mother and father of bioinformatics. And one of the key advances was the atlas of protein sequences structure, which was the first collection of all proteins that had been sequenced to date. I forget the exact number, but I think it was somewhere between 50 and 100. The 1970s, we start to see additional algorithms for alignments and the first efforts at sequencing, right? So Sanger plus minus, Maxim Gilbert, which I understand is a horrific way of sequencing. It's a chemical that's cream and toxic. And then the revolution in 1977 was the Sanger-dioxicane termination. He was translated over 64,000 times. This is what got him his second Nobel Prize in 1980. So the turnaround timer was like, okay, so this is significant. Also in 1977, the first major discovery of the Archaea, right? This sort of Karl Woglitz-George Fox tree of microbial life. Also in 1977, where is it? Oh, I don't have the other on the next slide, so we'll see that in a second. 1977, the Staten-Bioinformatics software. And the Staten package in 1979 added the first method for automated sequences, right? So 1979, the continuing rapid follow of the cost of computer components is making it possible for most DNA sequencing laboratories to have their own small computers. So the fact that DNA sequencing is now a fast procedure and the availability of computers gets the possibility of more efficient overall strategies in sequence determination. Holy crap, look at all the data, right?  So here is the chances, this is amazing. So 1970s, this is what I was gonna say. Genome sequence, 1977 by X, right? Now it's the genome that's more sequenced than any other, because you dump it into your my sequence, as well as some of these clustering issues. And so here in all this glory, make sure that we're going to look at 1975 and the whole genome. 48 years ago. This one's pretty neat too. So it was determined in 1974, 1975, 76, but it wasn't through sequencing. It was through really information analysis, right? Mutations, other really, you know, difficult and time consuming techniques. So this map is not based on DNA sequences, based on, you know, at least 20 years of experimental biology. These are the first. Okay, 1980s, 1980s. Dr. Deva, it's done with an online computer database and a sophisticated retrieval system accessible by phone to outside users in September 1980. So imagine, okay, and I don't know exactly how it works. That was three when it came out, but you call in, right? And you're like, press one for insulin. M, A, R, right? So yeah, I laughed, but it's remarkable. Okay, so we're getting to what I call the dawn of metagenomics, okay? Because in 1984, 1985, more recently, developed the first methods for sequencing genes from microbial communities without culturing, okay? This is where it all started. They did not sequence the seed in the gene. They sequenced the ribosomal RNA interaction, okay? But this is where it all began, okay? 1985, 30 years ago. To hydrothermal tests and then to talk to the spring with the industry, you know? mid-1980s, and this paved the way for everything that came after. The first data sharing agreement between NIH and US, EMBL and Europe, and JNIT and Japan, right? Let's mirror things, let's share the data, let's make it open. Thank you very much, right? By the geography, 1987, this is certainly playing an important role in various environmental metagenomics. 1989, ribosomal database project, right? So, they come along. On metagenomics, right? We have a couple of reference sequences from solapolivus, the student calderia, and the comodicus for the environmental sequences that were characterized on that. Very simple communities, but it was 1985. Holy moly. Right? 1990. CNES study. You have an on-ancient, cellular genome, 1995. Go ahead up to 1999. Who knows what a RISA is? Okay, what's a RISA? Ribosomal, yep. So, the basic idea is that it's really expensive to sequence, in fact. So, let's use restriction digestion and some sort of gel-based approach or some other-sized, typing-based approach such that, you know, your heterogenic transfer of sequence between 16S and 243, yeah. And mine are slightly different, but hopefully they have sequence variations that lead to differences in restriction sites. So, even very recently, you see papers published that are based on a RISA. Doesn't give you as much information as others do, and it can be difficult to do automatic attribution, but it's still what it is called. Okay, 2000 metapronium is called the Kepronium. People knew about it, and they got a little discovery of life-harvesting method of- Definitely, the microbiome. 2004, Prismus double, Acid-migrated metapronium, Gil-Batheal, Acid-migrated metatranscriptomics, Gil-Batheal. 2005, Acid-migrated metapronium, Gil-Batheal, right? So, she led the way in a lot of the stuff in the mid-2000s. So, it's a very, very deep sequence, starting to get into the human microbiome studies. And then the two major human microbiome, HFT, and then the European Medi-Hist Project. Okay, we're reaching the end for it. And so, more and more sequence variations on this policy, and that's a degree, many of you know of, has been probably the leader in the advancement of microbial ecology into the sequencing medicinal mix era. So, a lot of these sort of beta diversity methods, different statistics, different environmental correlates. In 2013, quickly biomephobiasylab, sequence, people samples from 21 mice. So, we do computational stuff, and we're like, hey, we have $6,000, what can we do with it, boom, right? So, this is just an illustration of how it's estimated to be coming. 2015, we're out of sources, and now we're working on it. And I, unreleased, we're getting ours in a few weeks, we're very excited. And the other thing about this decade is that with the greater accessibility of sequencing for very low cost, you start to see interesting things like the microbiome of roller girders, right? And that's actually, that's a good read. This thing, I'm not allowed to mention last year, this microbiome, mobile phones, American cool ship ale, Iron Rugby players, Mike just pointed me out to the sports surfaces microbiome, which was like workout tables and stuff like that. I can't do that. And retesional cheats, which actually I would love to have been involved in that. Okay, so that's history. History is history. Any questions so far? Apart from what are you gonna get to the point of? Any questions? Questions? Okay. Yeah, question. This is gonna answer. Who wasn't? Who was she? Anybody know? I forget. Sanger. So the early metagenomes, 10 years ago, the early metagenomes that you used to, these days, and I'm gonna show you an example later, roughly, is for doing them. So it's not restricted to Illumina or Pac-Bio or 454 or Nanocore or anything specific like that. So this is the very, very, very, very high level view of how these things are done, right? The big picture, the big picture, you have a sample of data. Well, this is the metagenomes, metatranscriptomes, metaproteomes, microgene, whatever, right? You've seen very important, I mean, this is one of the critical things of the early 2010s with the development. One of the papers that I included in your recommended package, which is your subword, Bioinformatics for the Human Microbiome Project, right? So this doesn't go into the details, but it cites the details. This is basically saying we had more data than anyone had ever dealt with before. We needed to do the analysis quickly and well, right? So they talk about some of the 16S analysis challenges they face and they did things like building mock communities. So basically, what's a mock community? It's like, okay, I have, in you go, in you go, in you go, what's on the show? Kidding me. Okay, see, I warned you, didn't I? Yeah, exactly. So, and then the downstream analysis. So, by the way, just very quickly, my plan was to go as far as I could before the coffee break or before I see that it gets to be very important product. And then after coffee break, so after you've been as coffee break, after coffee break, I figured we dive into the tutorial, maybe for an hour and then save the last half hour to finish up with this. I think that's a reasonable balance of things. Market teams extract DNA, amplify with targeted primers, right? You can look at B1, you can look at B2, B4, B3, B5, B69, filter errors, filter clusters. You don't know what I just said, you'll learn about it this afternoon. And then various types of diversity analysis. And if you don't see my B extract DNA, quality control, and then your various diversity function analysis, metabolic pathway reconstruction, what have you. Metatranscript filmics, which I'm very excited for Friday, because I haven't really done this myself. I've been really looking forward to John's session. Extract RNA, the ribosomal RNA, because, well, it's actually quite informative and Jessica Green had a great paper on how ribosomal RNA levels can actually cause many things to it, but it turns into function control. And then you can look at function gene expression, taxonomy, usual size. One of the papers that I'm gonna give a very brief overview of the metatranscript film can be orders of magnitude more informative than the metagenome. It's a detail, right? It's there pretty well. We're making samples and we're gonna have some metadata, which is like these samples in this ball. Let me be specific. These samples came from older mice, these from middle-aged mice, and these from younger mice. And so we have some sort of taxonomic representation. In this case, and again, you'll be learning about this this afternoon, so don't worry about it too much. It's a principle components plot. I think it's a principle coordinate plot. It basically tries to take all the diversity, smoosh it down into a couple of manageable dimensions, and then show you the similarity. Well, that's another matter entirely. Okay. Well, I have some papers to talk about. Michelle, how much time do I have? So just to kind of give some motivating examples of some really cool work that's been done in the last few years, I wanted to walk through a few different examples of metagenomics, metahomics. And I haven't put these papers up, but they are cited in the talk. And if I remember, which means if you remind me, I can also throw them up on the wiki later on. These are some of my favorite papers. Well, some of these are my favorites, and then a couple of them. So, it's always good when you're explaining metagnomics to your mom, dad, and neighbor to start a cluster that you didn't know. Because hey, that's one of the most prominent examples of the discovery, the use, the application, the success of essentially a metagenomic approach. The microbiome was from 2012, a pharmacogenic plebrololid at the Sanger Center and a cast of thousands, or at least a dozen or so, looked at, we had these different mice and we've taken samples from them. When you represented this way, there's sort of some captain obvious stuff going as a sign of the problem. But this is just the community profile. Who knows what Shannon diversity is? So Shannon diversity is, okay, so let me back the talk up for a second further and tries to use this information-based approaches to try and accommodate both the richness and the diverse, what's the diverse? It's the relative abundance, right? Because a richness of 10, where the distribution is 10%, 10%, 10%, 10%, 10%, 10%, 10%, 10%, 99%, 0.1, 0.1, 0.1, 0.1 and so on, right? And so Shannon diversity attempts to capture this. They're both informative measures, but they serve somewhat different purposes. And in this case, you can switch including the 90 mice and the covered mice have a much higher Shannon diversity than those of you who've looked at any papers like this, dysbiosis, things ain't going so bad in the gut, are usually succeeding in the gut. Now, this is like my favorite figure from microbiomics ever seen. And of course, it's a pretty cool component to why because you can't have a microbiome in the paper today. Go to the diversity information before. And again, Will's gonna talk more about this. What I've showed you before is the alpha diversity. What's the alpha diversity? It's simply the diversity within a second, right? And so you have an alpha diversity of your gut and you have an alpha diversity of the alpha. Beta diversity, which I'm sure some of you are familiar with others, maybe not, beta diversity assimilates similarly to the dissimilarity. And so if my gut microbiome and Yanan's gut microbiome are very similar, then our beta diversity is low. And so what they did here was they calculated the beta diversity between all pairs of samples and then they ran this through the principle. This is a different, I think Will is gonna start with the difference between principle points, principle coordinates this afternoon, he is now. Okay, so anyway, but the answer is, if you get this lower dimensional one, the trig cluster there, over here is just about right. We have very, or we can give them an antibiotic, say, clindomite, right? So let me explain what are the four different colors. And the other are a lot of the silks. So this is your probiotic yogurt, the yogurt that you eat in the morning with you. What is the classic one? What is mix B? Well, it's a subset, it's a chosen subset from the healthy microbiota. Because what's in the poop of a mouse? I don't know, you know, right?  Maybe not, mix B, they took six things. They put them together and they said, how well does this work? So these are classic, right? So this helps you mix B with the most successful. You've got sickness, you've got health, you've got different treatments. And actually the geography of this weird abstract plot thing tells you a huge amount of information, okay? So I think I'm at time for this morning. Okay, we'll do, okay? Hopefully people's brains are not full yet. Any questions about this? Okay, good, it's all clear. It all makes sense. All right, these are some of my favorite papers. And this one is, in my meta-genomics, the environments in ecology and the results are really nice. Yes, of course, thank you for the little selected and favorite circumstances. I'm not gonna call it a competition, but I'll give you a lot of the insights. And see the answers, I don't know. Because yeah, I mean, if passage worked well, then it makes sense to sub-sample from that one to try and get a simpler community. Absolutely. Any other questions about feeding various things to the rest of the questions? All right, I've got a field research point. So we like this so much, we actually implemented it in some of our software. Let me start by asking, is anyone familiar with canonical correlation analysis? Okay, how many of you are familiar with principle components beyond the thing I just showed you? So PCA is a mapping of these complicated patterns of diversity or function into a smaller set of dimensions that hopefully capture most of the information that you had before. But you can visualize because two dimensions is cool, right? 37,000 databases. And over here, this is membrane proteins, this is transporters. They focused on those specific changes in environmental conditions. That is why they focused on those. And so again, don't always think of all the dataset, focus on some of the greatest importance. So what are the two dimensions? You actually want to make sure that the variables digitalized together. You can see strong correlations between environment and the family and also technology for decades, okay? It's cool that they applied it, but they forgot to step further. Because no relation, maybe they're anti-covalent, you don't know. If they took these ordinance sections between those not in the software, what if the relationship between shipping and this phosphate transporter, right? I'll finish this one in there. So let's look at those numbers, those valuations. Let us draw an edge between them and let the green edges represent strong positive association. What do you end up with?  So this affects, there's a relationship. We shouldn't infer too much causality. There's a relationship between these things. And the phenotype environment network makes it very clear. Any questions about that? I have three more examples, but I think it's time for me to hand over to Geven. Questions? Thank you. Thanks, welcome back. So I just wanted to follow up with, I think Daniel had this question beforehand. This is from the mouse paper, right? And so Debra's collection of 18 bacterial species from the passive one fecal derivative. They had 18 different species, so-called. They split them into the three mixes. Mix A was six of them, mix B was six of them, and mix C was six of them. Dr. Seussian. And this is basically showing that mix A and mix C did not reduce the colony-forming units of C-diff. Mix B did, so that was the successful one. And then they characterized the six species in mix B. Staff worn awry into a caucus highway, lack of a cellist's droid awry, and then three novel species, species known, species known, species known. So that's the story of mix B. Okay, so I'm going to go through the remaining three examples a bit more quickly, hopefully. This is a very recently published, beautiful example of what you can do with metagenomes plus metatranscriptomics, both in terms of working up the data and interpreting the data. And I'm not going to do all of this. Like I said, I'll put the reference up if you can remind me later. The basic idea is that you have raw metagenomic and raw C-d, metatranscriptomic data, quality control. And what they did was interesting. So they split their metagenomes, because metagenomes are very complicated, right? Now this was an acid-mined drainage community, so it's a lot less complicated, but it's still complicated. There's still a few different things in there. They actually split their metagenome based on camber abundance. What's a camber? Who knows what a camer is? Camer, okay. So, somebody give me 10 letters of DNA. Come on. C, G. A, T. A, T. Stretch of A's. What's that? Stretch of A's. Ha, ha, ha. A, A, A. Seven, okay. T, I'm going to throw in a G, and? C. C, perfect. Okay, so this is a sequence of DNA. One way to figure out, one way to represent it is by doing a blast search, comparing it against database, and then trying to figure out what it matches to. Another way to deal with this is to decompose it into camers. So, camers are words of length K. So, if we want to express this in terms of camers of length two, camers of length two are dimers, right? And so, we can say, how many CGs do we have? Well, we have one. How many GAs we have one. How many ATs, one, two, right? So, you see how we're counting words of it given length. So, and we have two AAs, for example. So, that's the camer decomposition. You're just counting words of a certain length. Words of different lengths are useful for different purposes. Here they used words of length, oh, I think it was 12, but I forgot. And they basically separated them into high abundance words, which might come from high abundance species and low abundance words. So, they're taking their metagenome, and they're actually fractionating it out so that the resulting things are simpler. And then there's some garbage, left of, not garbage, but there's some leftovers that they scoop up and put back together. So, they get context that are theoretically better than you would just get from naive metagenome, right? They assemble their RNAs, they do clustering, and they build these context. They claimed 11 draft genomes from this AMD sample, which is pretty cool. So, what's really neat about this? In addition to that, is that, so here are 11 different things, the 11 species or types or whatever you wanna call them identified. These are the abundances, the relative abundances of their DNA, i.e. metagenome, versus cDNA, i.e. RNA, i.e. metatranscript, right? And so, you can see that FKV7, which is ferrovoom, ferrovoom, was over 98% of the DNA. And in transcriptional terms, it's about 92%. So, you get a relationship, you can see that sort of a naive assumption that DNA and RNA level should be the same. It's actually kind of under-producing, right? And then look at FKV1, it's way less than 1%, but its transcriptional contribution is over 1%. It's punching above its weight in functional terms. Makes sense? And so, there's the really, really common thing, and then there are the rare things. And here's the crucial outcome of the paper. There are critical functions, such as nitrogen fixation that are going on in the community. Who's doing them? The rare things, okay? FKV1, I don't know what's the example. Yeah, FKV1, right? Very rare, far less than 1% of the community, doing most of the nitrogen fixation, almost all of the nitrogen fixation coming from this one little dude, right? What is it? Acidithiobacillus ferrooxidant, which is interesting for a whole range of reasons, some of my favorite organisms. And then you can see sulfate reduction being carried out by FKV7, so that's pretty common. But then other functions, you can see that other rare individuals are carrying out certain other crucial functions, right? Metagenomics wouldn't really tell you this, necessarily. Metatranscriptomics does, yeah? Plus you get 11 draft genomes, so that's really cool. Okay, this is not as recent, but it's just a very quick example of metabolomics, or metataphylomics, in bacterial vaginosis. And I don't wanna dwell on this too much. It's basically showing you that there's more than one approach, right? And so what they had here, they had, I forget the exact number, but each of these was an individual, either negative for bacterial vaginosis or positive. And so this is a heat map, and we've all seen heat maps, right? Hotter colors represent higher amounts of somethings, right? And so this, there's really super red box here, it means that's zero for five. Individual 50, individual 50 has a lot of that metabolite. Mednailla, no, I don't know what that is. You get the idea, right? And so these are all metabolites that were profiled using NMR, right? Not genes, not transcripts, not proteins, metabolites, which is really cool, because you get some functional information at the kind of business end of the managing of the microbiome. So they have two main clusters, each of which comprises people with and without BD. And you can see immediately that some metabolites are critically important in distinguishing both this cluster and that cluster, and then BD positive, right? So here's an example of something that distinguishes. So on balance, they concluded that catabolic pathways for things like amino acids and peptides were overrepresented because of the products they found. So, nice example. And then they did taxonomy, because hey, you got to do taxonomy. These are the kind of good guys over here, the lactobacillus, lactobacillus, lactobacillus. And these are sort of the doctorate breakfast of other organisms that are not as nice. So just, again, metabolites by organism. All right, last one. So this is a great paper. And I think this is the preprint. I think the paper's actually 2015. So this was a paper by a large number of authors. Senior author was Marty Blazer, who was one of the best known microbiome types. And the purpose of this study was to investigate the effects of low dose antibiotics, specifically penicillin, on physiological and metabolic development of mice from birth, right? So lots of people are put on prophylactic antibiotics and things like that for various reasons, early in life, later in life, and so on. And the question is, what are the consequences of this? We know that you're beating down certain parts of the microbiome when you do this. What are the effects, right? So they went a lot further, they went a lot further than just characterizing the microbiome. You need to look at this paper. It's got five figures and a total of 92 panels. I was like, what crucial panel can I pull out? So I chose the best 10. But here's the experimental design, basically. Control, right? No antibiotics. This is gestation, nursing, and then normal rat chow or mouse chow. Control, no antibiotics. LDP and weaning, blue, right? So the antibiotics started here at four weeks. And the B was birth, basically a little bit before birth. So during nursing and through mouse chow, they got the Lotus antibiotics. And then they characterized things in a billion ways, right? And just let me draw your attention to a couple of things. Growth rates were different. Where's the critical one at? Fat mass, right? So male and female mice, they found that the fat mass was significantly higher for the LDP group from birth. And they found different diet responses and so on and so forth. And so this is really interesting because they're looking at causal mechanisms. They're looking at these relationships, not just who's there, but what are the effects? So that's kind of interesting. And they let's get some taxonomy going, right? And so they had, these are the low-dose penicillin in red. This is the control group. And this is simply a phylogenetic tree with all the dudes they found, bacteria that is. And red is overrepresented in LDP and green is overrepresented in control. And so you can see, for example, that FS247G, I love the LDP taxonomy, is overrepresented in the low-dose penicillin, whereas other things over here, for example, are overrepresented in controls. So you get taxonomic views, but they have histology and they have physiological assays and all sorts of things. So it's in cell, it's quite a remarkable paper. I strongly encourage you to look at it. Okay, so let's do another quick survey. So you're doing data analysis, that's cool. How many people have used Sanger data? Nice, most of you, that's great. Ion torrent, okay, a couple of you, very nice. Roche, 454, yeah, yeah, a classic. Illumina, something seek, high seek, my seek. Nice, okay, so there's your market share right there. The PacBio multiple freezers stacked on top of each other. Yeah, nice. And then the Oxford Nanopore. Ask me in a couple of months, I'm very excited. Michelle? Cool. Okay, so obviously in choosing a sequencing technology there are many, many, many, many trade-offs such as sequence read length, right? So who's the winner? Depends on what you're doing with it. So arguably, so I think in terms of claim read length, one, two, three, four, five, six. So does anybody disagree with that? So Nanopore longest PacBio next, then Sanger, then 454, then Illumina, then Ion torrent. Illumina, Ion torrent, I kind of tied, I think. My seek may exceed the Ion torrent. Accuracy, we care about accuracy, right? So what's the most accurate? The most accurate. Illumina, Sanger, I think it's Sanger, right? So Sanger's pretty good. And then I think Illumina 454, pretty simple, I think. Depends what you want in accuracy. Of course, yeah. I mean, it's sort of, you know, you've got the generally reported error parameters and then there's different ways to run these things, different modes, different levels of accuracy. So I think in general, these three, 454 Ion torrent, Illumina, you can kind of run to roughly the same error level. And then we have the last two, right? Packed Bio, which gives you super long reads, and Nanophore, which gives you ultra long reads, but the error rates in both cases are still hovering around 10%, depending on which papers you read and who you listen to. And so, depending on your purpose, different examples of these will be most suitable. So what would you use to sequence a genome, for example? Because we love genomes. It depends on your genome. Okay, pick a genome. So we have saying in 454, Illumina and Pac-Bio, for two and a half times the size of the human, and how to put it. Which genome is that? Calculative proof and 3% of this microblast, it's not finished, that's the problem. Okay, so you're finishing it with a range of technologies, yeah. So all paths, the assembly algorithm combines, the latest version I know of, combines Pac-Bio with paired end Illumina with made paired Illumina, if I recall correctly. So you've got paired end reads that are close to each other, paired end reads that are long away from each other, and then the Pac-Bio long reads, which are much more error-prone. So in general, if you want really good quality something, you typically don't have one that gives you everything you want, right? And so a lot of people choose Illumina, hey, it's cheap, it gives a lot of data, it's reasonably accurate, and especially with a MySeq, you can get some level of assembly, right? But these are all very important considerations. Pac-Bio seems to have settled in a certain error profile. Nanopore is getting better all the time, and people are developing new algorithms to better interpret the signals as they come off the machine.  I have no idea. Will we still be talking about metagenomics in five years? I have no idea. So the thing we're gonna almost finish with, and then we're gonna explore in the tutorial a little bit are different resources. I'm just gonna run through these very quickly. So 16S, right? I mean, 16S has been the de rigueur gene of choice ever since Carl Woz and George Fox and so on said, let's sequence something, right?  And so these repositories, as I showed you, have been in place in a formal way since the late 1980s. RDP and silver and green genes all have, I think over a million sequences in them. Green genes is interesting because of its automated approach to taxonomy, right? And so as you'll see in the tutorial, if you take the same data set and you feed it through green genes, silver, or RDP2, you will get someone different conclusions. In the example I've given you, you will get very different conclusions as to whether a sample contains eukaryotes or not.  This is the RNA, a Rebson RNA copy number database. What is the largest copy number of 16S genes known in any organism to date? What's that? 16. I know a 15, what has 16? I don't know, I just read it. Okay, 15 I think is the record and of course I'm blanking on which organism it is, but many E. coli's typically have I think six or seven Rebsomal operons, right? And so you're gonna learn about PyCrust, which is predicting functions from taxonomy. And in general, if you have a taxonomic profile, an organism that has seven Rebsomal RNA genes is gonna be overrepresented because it has seven, as opposed to the ones that have a single copy. Most things have single copies. Most things that have more than one copy, if you build a tree with a bunch of things, their copies will cluster together in the tree and do a claim, so it's like, okay, these are all representative of Candidata Surangium celluloseumsoci and they're all kind of here, right? Halo Archaea can have 16S that diverge by greater than 10%. Where do they go in the tree? Don't ask me. Okay, genomes, right? Because genomes are the things from which meta-genomes are constructed. GenBank is a good resource, of course. Lots of modes of access and sort of the default place to put genomes, although they're not all there now. Gold is really nice because it has information. It's designed to adhere to some of these minimal standards for a sequence specification, right? We haven't talked about metadata quality, but you should try to have some, right? And so gold has a wide range of fields to say, where was it extracted from? What was the method used to sequence it and so on? So that's very good. Gold has been around forever. Patrick is the pathogen resource, so they have a nice set of features as well, including trees of different organisms. And then ensemble has both eukaryotic and prokaryotic genomes as well. And there's no shortage of resources. There are others as well. We're not doing a comprehensive survey. I'm just kind of introducing you to a couple. Okay, metagenomes. So this is one I have less experience with, but Mike has been using a lot of it. So if you have questions, I encourage you, like he's been using it at sort of the basic level to query things, APIs and things like that. EBI is pretty good for that. MG Rast also has a really nice API and we will be looking at that one in the tutorial, including what an API is. And then one that we've used to fair bid is the Human Microbiome Project Data Analysis and Coordination Center, the HMP DAC, which has all of the HMP data, right? Metadata, 16S, Metagenome Reads, Metagenome Assemblies, you name it, right? It's all there. And so there are big questions about the size of the database, the reliability of the database, the completeness of the database, how do you access the database, right? So we're gonna look at a few of those things, okay? Function, so function is a great term because nobody knows what function means. Nobody knows how to define it. Nobody knows how to predict it because even the best characterized genomes typically have about 30% hypothetical proteins, right, the predicted hypothetical proteins. And if you're familiar with the snowys at all paper 2009, even the ones that have functional annotations are sometimes wrong. And if for some functional categories, they're always wrong, right? And so the key trade-off in looking at a functional database is coverage versus accuracy, okay? And so keg is an example of high coverage, but not the best accuracy. Actually, I talked about the snowys at all paper in a moment, but then you have Uniprot KB is neat because there's the SwissProt side and there's the tremble side and the SwissProt, as far as I know, is the most highly curated, the most accurate, most reliable resource for protein function. Therefore, its coverage is the smallest, right? Stands to reason. And then there's Uniprot KB tremble, which is more sort of predicted functions which gives you greater coverage at the cost of slightly lower accuracy. Genontology has decent coverage. One of the really nice things about Go is that you get evidence codes. So it tells you the function and tells you where that function came from, right? So there's inferred from direct assay or something, right? Experimental validation, and there's different classes of that. All the way down to person came back to the lab after a pub crawl, ran blast, hopefully with the right settings and assigned a function that came from E. coli via salmonella, via citrobacter, via staphylococcus to halo-pointer atom wall GI, right? So there's sort of that range of evidence codes. You can say, for this analysis, I'm gonna focus on the things that had experimental evidence, right? Card is new and very cool. This is the antibiotic resistance gene database. This is being developed by Andrew, it'll come to me, Andrew at McMaster University, MacArthur, that's it, Andrew MacArthur. And so it's meant to be a highly curated, highly accurate resource for antibiotic resistance genes. Obviously something that's getting a lot of attention these days. Okay, so, questions? I have one last section before we get into the tutorial, but I'm probably going pretty fast, so feel free to stop me and ask questions. Michelle, yes, five minutes. Okay, major concerns in metagenomic analysis, right? Here's one, right? Data quality, so we talked a bit about errors, right? So there's error rates, which are often quoted, and then there's error types, right? So some sequencing platforms get gummed up on, you know, tracks of a certain type of nucleotide. Others have attended to induce more insertions and deletions, some have biases in favor of certain types of call. So this is something that can really influence your results as well. And then there are the chimeras, right? And so those of you who have worked with 16S data are hopefully familiar, hopefully familiar with things like chimeras layer, for example, or bolerophonol, I think that one's a bit older, because if you're PCRing, if you were to find that, a bunch of 16S genes, often during the process, you'll get recombination, right? You'll get these chimeras, these hybrids, yeah. I was just wondering, when you were working with them, are you, is there a trend towards more labs and do they do a reducing strategy to work with them? Which I wish I was doing with my work. Not to my knowledge, I'm not sure, actually. This is a really good question. So is anyone using the deletion indexing approach? I know Pat's published on it. Pat's lost? Yeah. Okay. I think most people are still using the trend defaults, I think. But yeah, that's a good question. All right. Comparability, reproducibility. There was a paper, and I can't remember, I think it was from the Rob Nature, I think there have been a few papers, but the one I remember was that one, where a bunch of metagenome sequence from a bunch of different samples, and you run your piece, peek away, and you get to show me several of these plots already, and I can say what cluster is right. And it was one of those cases where they had 454 and Illumina data. And the primary criterion for clustering is whether the sample had been sequenced using 454 or Illumina, right? And so one thing that I really like to do is meta-analysis, combining many data sets. And with sequence genomes, especially finished genomes, this is kind of okay, although there are still assumptions. But if you're trying to grab a whole bunch of 16S, or particularly metagenomic data, or metatranscriptomes, if you can find them, the sequencing platform can have a huge impact on the results you get, right? This is true with 16S with different variable regions, right? People have done studies where they're like, you know, your diversity profile is like this, if you do V13, and like that, if you do V35, right? So that's a problem. And I meant to include a citation to this. I'll add that to the website. But basically, building some of these mock communities and then trying different extraction strategies, DNA extraction strategies, and different sequencing strategies, you know, whether it's Amplicon-based or Shotgun-based, and getting very different characteristic results in the outcome, whether they were able to recapture the community or not. And then, you know, read the methods section. We use Chine version 2.3.6 point upside on happyface.apps, Ampersand, which uses UCLUS version this, which uses, you know, RDP version 15, release 15, whatever. Reproducibility is a massive, massive thing, right? There are solutions like Galaxy for workflows, which really, you know, do encourage reproducibility. Several people have written about reproducibility of bioinformatics analyses in general. I strongly encourage you to look those things up and try to adhere to them as much as you can, as well as making your data public, but you already knew that. This is my favorite example. OK, I'm almost done, almost done. And so this is, so Morgan's presenting the metagenomic stuff more. This is our mouse booth study. I showed you a very similar plot earlier. I apologize for the loss being so small. But we had 21 samples, OK, from 21 mites, the old Middle Age and young. So a very, very small study, right, a pilot. And we said, all right, we can do these comparisons. But wouldn't it be nicer if we had a larger reference data set? OK, we'll compare them against a larger set to see how they stack up. We're like, well, people have sequenced mouse poop all over the place, right? It's like it's a giant cottage industry. There was even a paper where they sequenced the fecal microbiome of five or six different healthy mouse strains compared to, of course, their mouse strain effects. So that's great. So I asked Morgan and my other postdoc at the time, Conner, to grab these other data sets, put them with our 21 samples, and then do like a pico-a analysis and see whether the old or the young or the Middle Age tended to cluster more closely with the mice that people would see, but most pooped the people in sequenced earlier. And guess what? The reference, although the reference sequence is often occupied as a little part of the plot, and ours are like, boom, all over the place, right? Comparability? No. Wouldn't it be nice? But it's a bit of a fantasy. I mean, we could have tried harder and gone back to the raw sequences and tried to sort it out, but even then, we'd probably just be asking for trouble. Okay, linkage and resolution, strain-level diversity is often missed by Amplicon shotgun approaches, and in many cases, strain-level diversity is crucial. Often whether your wastewater treatment plant works or not depends on which strain of Candidatus, Acumulobacter, Phosphatus, your house. Does 16S resolve this? No. Does polyphosphate kinase, an alternative marker gene, resolve this? Yes. 16S gives you a certain level of resolution. The intergenic spacer between 16S and 23S gives you more resolution. Long story short, paper from 2009, and they found that if they clustered these ITS, these more variable sequences, right there, if they differ from each other more, these are all from Prochlorococcus meridus, the fourth organism in the ocean. If you cluster at about 97 to 99%, you find strong associations between taxonomic diversity and nitrate concentrations in the ocean. If you cluster at 90% identity, you get associations of light, 95% temperature, and so depending on your taxonomic resolution, you can actually find associations with different environmental variables. RDP taxonomy is hideous, but we live with it anyway. Well, you'll be hearing enough about operation taxonomy that's there, there are uses, but again, we use them.  We can talk about this later. This is the critical assessment of functional annotation. Functional prediction methods for proteins, not doing so well, getting better, but there are some limitations there. So all these hypotheticals, still very difficult to predict. Okay, so in conclusion, we're on a coffee break in networking session, no we're not. I'm gonna give you a minute. If you have questions, please feel free to ask them. We're gonna take a deep breath and then we're gonna move into the tutorial.