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2f:{"title":"Computing Root-to-Tip Distances with Phylotree.js","cells":[{"id":0,"value":"md`# Computing Root-to-Tip Distances with Phylotree.js\n\nComputing root-to-tip distances and plotting them against time can help determine whether there is a strong temporal signal within a constructed tree. It is especially common to utilize a root-to-tip vs. time plot when researching the phylodynamics of a particular virus.\n\nIf the tree exhibits a positive correlation between genetic divergence and sampling time, the dataset may be appropriate for phylogenetic molecular clock analysis.¹ We will investigate if that is the case with our supplied tree by performing linear regression on root-to-tip distances vs. collection date.\n\n`\n\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":234,"value":"md`## Selecting a newick tree\n\nHere, we will use a tree that was part of a study on the transmission of Middle East respiratory syndrome coronavirus (MERS) from camels to humans.² The coronavirus was first detected in patients from the Arabian Peninsula in 2012. The tips of the tree were annotated with both host and collection date attributes.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":483,"value":"md `## Initial rendering of the phylogenetic tree given the newick tree`","pinned":false,"hidden":false,"mode":"ojs"},{"id":250,"value":"viewof height = slider({\n min: 400,\n max: 5000,\n precision: 1,\n value: 2200,\n description: \"Height\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":12,"value":"viewof width = slider({\n min: 800,\n max: 5000,\n precision: 1,\n value: 800,\n description: \"Width\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"tree = new phylotree.phylotree(nwk);","pinned":false,"hidden":false,"mode":"ojs"},{"id":597,"value":"tree.getTips()","pinned":false,"hidden":false,"mode":"ojs"},{"id":596,"value":"rendered_tree = tree.render(\"#tree_container\", {\n height:height, \n width:width, \n 'left-right-spacing': 'fit-to-size', \n 'top-bottom-spacing': 'fit-to-size'\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":161,"value":"html`\n \n

\n `","pinned":false,"hidden":false,"mode":"ojs"},{"id":481,"value":"md`## Computing root-to-tip distances\n\nOnce the function root_to_tip is called given the tree object, all tips within the tree should have a new attribute entitled root_to_tip`","pinned":false,"hidden":false,"mode":"ojs"},{"id":153,"value":"computed_tree = {\n phylotree.rootToTip(tree)\n return tree;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":490,"value":"md`Verifying that each tip has the attribute root_to_tip`","pinned":false,"hidden":false,"mode":"ojs"},{"id":171,"value":"tips = computed_tree.getTips()","pinned":false,"hidden":false,"mode":"ojs"},{"id":493,"value":"md`## Parsing the date from the header\n\nIn order to plot root-to-tip distances against time, we will need to parse the dates from the node names. phylotree_utils provides a convenience function, extract_dates, to extract dates from the node names and place them in new attributes, decimal_date_value and date_value, in each named node.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":504,"value":"md`Declare a callback function to extract the dates.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":359,"value":"date_parser = function(node) {\n const default_regexp = /([0-9]{4})-?([0-9]{2})-?([0-9]{2})$/g;\n if (tree.isLeafNode(node)) {\n if (\"name\" in node.data) {\n var location = default_regexp.exec(node.data.name);\n if (location) {\n return location[1] + location[2] + location[3];\n } else {\n const default_regexp = /([0-9]{4})-?([0-9]{2})$/g;\n var location = default_regexp.exec(node.data.name);\n if (location) {\n return location[1] + location[2] + '1';\n }\n }\n \n }\n }\n return null;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":438,"value":"tree_with_dates = phylotree.extract_dates(computed_tree, date_parser)","pinned":false,"hidden":false,"mode":"ojs"},{"id":353,"value":"date_and_distances = {\n const mapped = _.map(tree_with_dates.getTips(), d => {return _.pick(d.data, [\"root_to_tip\", \"decimal_date_value\", \"date_value\"])});\n \n // Filter just in case the date extractor did not always find a date from the header\n return _.filter(mapped, d => { return !_.isNull(d.decimal_date_value) })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":506,"value":"md `## Root-to-tip linear regression`","pinned":false,"hidden":false,"mode":"ojs"},{"id":432,"value":"fitted_slope = phylotree.fitRootToTip(tree_with_dates)","pinned":false,"hidden":false,"mode":"ojs"},{"id":624,"value":"computed_tree","pinned":false,"hidden":false,"mode":"ojs"},{"id":444,"value":"pred = _.map(_.map(date_and_distances, d => { return d.decimal_date_value }), function(x) {return fitted_slope[\"fit\"][\"intercept\"]+fitted_slope[\"fit\"][\"slope\"]*x;})","pinned":false,"hidden":false,"mode":"ojs"},{"id":254,"value":"rttplot = {\n var trace = {\n type: \"scatter\",\n mode: \"markers\",\n x: _.map(date_and_distances, d => { return d.decimal_date_value }),\n y: _.map(date_and_distances, d => { return d.root_to_tip }),\n text: _.map(date_and_distances, d => { return d.date_value }),\n marker: {\n size: 5,\n color: \"red\"\n },\n name: \"Observed\"\n }\n \n var ptrace = {\n type: \"scatter\",\n mode: \"line\",\n x: _.map(date_and_distances, d => { return d.decimal_date_value }),\n y: pred,\n marker: {\n size: 5,\n color: \"black\"\n },\n name: \"Fitted\"\n }\n \n var data = [trace, ptrace];\n \n var layout = {\n title: 'Root-to-tip vs collection date',\n width: 800,\n xaxis: {tickvals:[\"2012\", \"2013\", \"2014\", \"2015\", \"2016\"]},\n };\n \n const div = DOM.element('div');\n plotly.newPlot(div, data, layout);\n return div;\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":527,"value":"{\n return html`R² = ${d3.format('.3f')(fitted_slope.fit.r2)}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":541,"value":"md`When inspecting R², we see that there is a reasonably strong association between genetic distances and sampling dates. We can feel confident that the tree is suitable for phylogenetic molecular clock analysis in BEAST or other programs. Determining whether to use a relaxed or strict clock may be best left to further model selection methods.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":469,"value":"md `## Table of Root-to-Tip Distances`","pinned":false,"hidden":false,"mode":"ojs"},{"id":176,"value":"table(_.map(tips, tip => { return _.pick(tip, \"name\", \"root_to_tip\")})) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":224,"value":"md` ## References\n\n1. Rambaut, Andrew, et al. \"Exploring the temporal structure of heterochronous sequences using TempEst (formerly Path-O-Gen).\" Virus evolution 2.1 (2016): vew007.\n\n2. Dudas, Gytis, et al. \"MERS-CoV spillover at the camel-human interface.\" ELife 7 (2018): e31257.\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":260,"value":"md`## Dependencies`","pinned":false,"hidden":false,"mode":"ojs"},{"id":14,"value":"html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":569,"value":"import {slider} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":186,"value":"import { table } from \"@gampleman/table\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":209,"value":"_ = require(\"lodash@4\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"d3 = require(\"d3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":564,"value":"phylotree = require('phylotree@1.0.0')","pinned":false,"hidden":false,"mode":"ojs"},{"id":256,"value":"plotly = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}