Hi. We're going to learn how to do one of my favorite functions with the heatmap, which is called the anchoring. Let's launch it and then I'll describe how to do it. Up here on the "Anchor" icon, let's click on that. Let's select the genome. I want to select the Brucella microti genome isolated from mice. While this is loading, let me describe what it does. It's going to reorder the protein families in the order that they occur on the microti genome. Brucella have two chromosomes. It's going to start with the first chromosomal microti, and it's going to call on the first gene. If I scroll this open. This particular gene, the plasmid replicon protein is the first called protein in Brucella microti. This is the second, the third, the fourth, and so on. It's reorienting the heatmap view dependent upon that. It's not messing with the order of the genomes, just the protein families. Right away, you can see patterns start to emerge. Let's open this a bit. You can see some genomic islands that are well-known in the Brucella, this one is called the [inaudible] island. If I go down to microti, you can see a number of protein families that are here. Because this is in microti, I know that they're next to each other. This is a large block of genes that are missing. So let's look at who's missing them. They're missing in the abortus genomes that looks like, except for this one, happens to have a few of them. But the large block seems to be missing in all the abortus. Here's another group. You notice that it's highlighting on the vertical axis of the genomes that I'm going over. This is the melitensis group. They're also missing this block. If I were to scroll down, you can see that it's missing in this pinnipedialis group, which will isolate it from seals. These particular two genomes. This one was isolated from a human. It was very [inaudible] one and this one from suis biovar 5. One of the things that often you have happened with a really nice visualization is I can see the data. Here, I can see what it is. But if I scroll over it, I can see what its name, but I can't capture that data. How can I capture that? I mean, if I have to bite down all of these PL fans, it's going to take me the rest of the day. I would hate to have to do that. But watch my cursor. Now, I'm drawing, you see that blue square drawn over that in the microbial genome that matches that area. Then it's going to open a pop-up window that asks me what I want to do with this data. I can download the heatmap data or the entire heatmap. I can download those proteins. I can show those proteins, or I can add those proteins to a group, or I can cancel it. I want to show what those proteins are. Let's click on "Show". This gives me a list of the proteins that I captured from that heatmap. Notice that I said we were walking down the genome of Brucella microti in the genes that were annotated here. This is the ID for this particular gene in PATRIC that belongs to this local family and this global family. Notice the genome might be here. Remember at one point, we talked about unique identifiers in PATRIC for particular genomes; that identifier is here. This is telling me that this gene belongs to Brucella microti. Then it's got a peg number, which is just our identifier for a particular gene and this is 349. This is the 349 gene in that genome, 50, 51, 52, 53, 54, all the way down to 65. These correspond to this area in this genome. That is a really cool functionality. Next time, I'm going to show you how we can drill into specific genes and find out more information, not only about the gene from this table, but also looking at a gene neighborhood and figuring out how tightly conserved it is. Thanks for watching, and thank you for using PATRIC. Bye. I've had to keep that port tab opened a long time and you're going to have to close it. But before you do, in this last segment, you learned how to download data from the heatmap. Well, it's still clustered. You've got those Canu genomes and you've got those Unicycler genomes. Last time you notice that there were Canu genomes with zero Racon iterations and 1-4 Pilon iterations that had some differences compared to everybody else. I want you for one of those genomes, draw that box over those particular proteins. Then when the pop-up box comes up, say show proteins, which will open a new tab, do the same thing for one of the Unicycler genomes in the same area that have a different color. I think we're talking about yellow versus orange, or it might be yellow versus tangerine. You'll have two tables open up on two separate tabs; one is the Unicycler data, one is the Canu data. One from the Canu data when you're looking at, are going to be seeing those genes now. Do any of those genes have the same name? Exactly the same? If you or the functional description. If you look at the gene identifier that has that big with the genome ID, peg with the gene number, what are those numbers? What does that imply for those? What do you think that exactly means? For the Unicycler for the same genes that had the same name, how many do they have? What conclusions can you draw from that particular data? Then after you finish that assignment, it's time to re-do the protein families sorter, and we're going to anchor this time. But for some reason, anchoring, you can't do it on top of a clustering. You have to go in and, once again, go back to the interface to load it. Canu, genomes, group, Unicycler, genome group, pg fams, launch for things. Then I want you to anchor the heatmap view on the Canu assembly with zero rack on iterations and one Pilon iteration. Do you see any patterns in the data when it's anchored that way, especially in the first annotated genes? Secondly, select that group of genes from the heatmap and click the "Show proteins". Then do the same for the section of proteins from the genome that was assembled from Unicycler. Don't close this tab because we have more to do. There still more assignments to go. I know that you're very excited. You never want this to end. It seems like it's never going to end, but it is eventually. That we're all building up to the huge crescendo of what do these assemblies mean, and what is truth when it comes to assembly and annotation. Good luck with this assignment, and I'll see you in the next segment.
