31:T982,tabulatedView=html`

${data.input["number of sequences"]} sequences in the alignment	${data.input["number of sites"]} sites in the alignment
${d3.format(".1f")(data["fits"]["Unconstrained model"]["Log Likelihood"])} Unconstrained model log L	${d3.format(".1f")(data["fits"]["Unconstrained model"]["AIC-c"])} Unconstrained model cAIC	${d3.format(".2f")(data["fits"]["Unconstrained model"]["Rate Distributions"]["Test"]["2"]["omega"])} Unconstrained model w3 value	${d3.format(".2f")(data["fits"]["Unconstrained model"]["Rate Distributions"]["Test"]["2"]["proportion"])} Unconstrained model p3 value
${d3.format(".1f")(data["fits"]["Constrained model"]["Log Likelihood"])} Constrained model log L	${d3.format(".1f")(data["fits"]["Constrained model"]["AIC-c"])} Constrained model cAIC	${d3.format(".2f")(data["fits"]["Constrained model"]["Rate Distributions"]["Test"]["2"]["omega"])} Constrained model w3 value	${d3.format(".2f")(data["fits"]["Constrained model"]["Rate Distributions"]["Test"]["2"]["proportion"])} Constrained model p3 value

`32:T100a,renderTwoDiscreteDistributions = (data, data2, options) => { options = options || {}; options.width = options.width || 200; options.height = options.height || 50; options.x = options.x || "omega"; options.ref = options.ref || [1]; options.ticks = options.ticks || 10; options.w = options.w || "proportion"; options.label = options.label || null; options.scale = options.scale || "linear"; options.margin = options.margin || {top: 5, right: 20, bottom: 20 + (options.label ? 12 : 0), left: 20}; const x_range = d3.extent(data, d => d[options.x]); x_range[1] = Math.max (1, x_range[1]); const x = (options.scale == "sqrt" ? d3.scaleSqrt() : (options.scale == "symlog" ? d3.scaleSymlog () : d3.scaleLinear())) .domain(x_range).nice() .range([options.margin.left, options.width - options.margin.right]); const y = d3.scaleLinear() .domain([0,1]).nice() .range([options.height - options.margin.bottom, options.margin.top]); options.size = options.size || ((d)=>Math.sqrt(d)*(y.range()[0]-y.range()[1])*0.25); const xAxis = g => g .attr("transform", `translate(0,${options.height - options.margin.bottom})`) .call(d3.axisBottom(x).ticks(options.ticks)); const yAxis = g => g .attr("transform", `translate(${options.margin.left},0)`) .call(d3.axisLeft(y)); const svg = d3.create("svg") .attr("width", options.width) .attr("height", options.height); const axis_object = svg.append("g") .call(xAxis); if (options.label && options.label.chart) { axis_object.append('text') .style('fill', 'black') .text(options.label.chart) .attr('x', options.margin.left + (options.width - options.margin.left - options.margin.right) / 2) .attr('y', 30); } if (options.label && options.label.series) { svg.append('text') .style('fill', 'black') .text(options.label.series[0]) .attr('x', options.width - options.margin.right + 5) .style ('font' , '12px courier') .attr('y', y (0.25)); svg.append('text') .style('fill', 'black') .text(options.label.series[1]) .attr('x', options.width - options.margin.right) .style ('font' , '12px courier') .attr('y', y (0.75)); } _.each ([data, data2], (dd,i)=>{ svg.append("g") .selectAll("circle") .data(dd) .join("circle") .attr("cx", d => x(d[options.x])) .attr("cy", d => y(0.25+i*0.5)) .attr("r", (d)=>options.size (d.proportion)) .style ("fill", "lightgrey") .style ("stroke", i == 0 ? "firebrick" : "steelblue" ) .style ("stroke-width", "1") .style ("fill-opacity", 0.2) .append ("title").text ((d)=>"" + d[options.x] + " (" + d[options.w] + ")"); }); const paired = _.map (data, (c, i)=> { return { 'x1' : c[options.x], 'x2' : data2[i][options.x], 'w1' : c[options.w], 'w2' : data2[i][options.w] }; }); svg.append("g") .selectAll("path") .data(paired) .join("path") .attr ("d", (d)=> { return "M " + (x(d.x1) - options.size (d.w1)) + "," + y(0.25) + " L " + (x(d.x1) + options.size (d.w1)) + "," + y(0.25) + " L " + (x(d.x2) + options.size (d.w2)) + "," + y(0.75) + " L " + (x(d.x2) - options.size (d.w2)) + "," + y(0.75) + " Z"; }) .style ("fill", "grey") .style('stroke', 'black') .style ("stroke-width", "0.5") .style ("opacity", 0.5); svg.append("g") .selectAll("line") .data(options.ref) .join("line") .attr("x1", d => x(d)) .attr("x2", d => x(d)) .attr("y1", d => y(0)) .attr("y2", d => y(1)) .style ("stroke", "firebrick") .style ("stroke-width", "2") .style ("opacity", 0.5); return svg.node(); }33:T1022,renderTwoDiscreteDistributions_SRV = (data, data2, options) => { options = options || {}; options.width = options.width || 200; options.height = options.height || 50; options.x = options.x || "rate"; options.ref = options.ref || [1]; options.ticks = options.ticks || 10; options.w = options.w || "proportion"; options.label = options.label || null; options.scale = options.scale || "linear"; options.margin = options.margin || {top: 5, right: 20, bottom: 20 + (options.label ? 12 : 0), left: 20}; const x_range = d3.extent(data, d => d[options.x]); x_range[1] = Math.max (1, x_range[1]); const x = (options.scale == "sqrt" ? d3.scaleSqrt() : (options.scale == "symlog" ? d3.scaleSymlog () : d3.scaleLinear())) .domain(x_range).nice() .range([options.margin.left, options.width - options.margin.right]); const y = d3.scaleLinear() .domain([0,1]).nice() .range([options.height - options.margin.bottom, options.margin.top]); options.size = options.size || ((d)=>Math.sqrt(d)*(y.range()[0]-y.range()[1])*0.25); const xAxis = g => g .attr("transform", `translate(0,${options.height - options.margin.bottom})`) .call(d3.axisBottom(x).ticks(options.ticks)); const yAxis = g => g .attr("transform", `translate(${options.margin.left},0)`) .call(d3.axisLeft(y)); const svg = d3.create("svg") .attr("width", options.width) .attr("height", options.height); const axis_object = svg.append("g") .call(xAxis); if (options.label && options.label.chart) { axis_object.append('text') .style('fill', 'black') .text(options.label.chart) .attr('x', options.margin.left + (options.width - options.margin.left - options.margin.right) / 2) .attr('y', 30); } if (options.label && options.label.series) { svg.append('text') .style('fill', 'black') .text(options.label.series[0]) .attr('x', options.width - options.margin.right + 5) .style ('font' , '12px courier') .attr('y', y (0.25)); svg.append('text') .style('fill', 'black') .text(options.label.series[1]) .attr('x', options.width - options.margin.right) .style ('font' , '12px courier') .attr('y', y (0.75)); } _.each ([data, data2], (dd,i)=>{ svg.append("g") .selectAll("circle") .data(dd) .join("circle") .attr("cx", d => x(d[options.x])) .attr("cy", d => y(0.25+i*0.5)) .attr("r", (d)=>options.size (d.proportion)) .style ("fill", "lightgrey") .style ("stroke", i == 0 ? "firebrick" : "steelblue" ) .style ("stroke-width", "1") .style ("fill-opacity", 0.2) .append ("title").text ((d)=>"" + d[options.x] + " (" + d[options.w] + ")"); }); const paired = _.map (data, (c, i)=> { return { 'x1' : c[options.x], 'x2' : data2[i][options.x], 'w1' : c[options.w], 'w2' : data2[i][options.w] }; }); svg.append("g") .selectAll("path") .data(paired) .join("path") .attr ("d", (d)=> { return "M " + (x(d.x1) - options.size (d.w1)) + "," + y(0.25) + " L " + (x(d.x1) + options.size (d.w1)) + "," + y(0.25) + " L " + (x(d.x2) + options.size (d.w2)) + "," + y(0.75) + " L " + (x(d.x2) - options.size (d.w2)) + "," + y(0.75) + " Z"; }) .style ("fill", "grey") .style('stroke', 'black') .style ("stroke-width", "0.5") .style ("opacity", 0.5); //svg.append("g") // .selectAll("line") // .data(options.ref) // .join("line") // .attr("x1", d => x(d)) // .attr("x2", d => x(d)) // .attr("y1", d => y(0)) // .attr("y2", d => y(1)) // .style ("stroke", "firebrick") // .style ("stroke-width", "2") // .style ("opacity", 0.5); return svg.node(); }34:T820,function multiAutoSelect(config = {}) { const { value, title, description, disabled, autocomplete = "off", placeholder, size, options, list = "variants" } = Array.isArray(config) ? { options: config } : config; const optionsSet = new Set(options); const form = input({ type: "text", title, description, attributes: { disabled }, action: fm => { const addSelectedOption = d => { const ele = html`${d} `; ele.querySelector("button").addEventListener("click", b => { fm.value.splice(fm.value.indexOf(d), 1); renderSelection(); fm.dispatchEvent(new CustomEvent("input")); fm.input.focus(); }); return ele; }; function renderSelection() { fm.output.innerHTML = ""; for (let o of fm.value) { fm.output.appendChild(addSelectedOption(o)); } } fm.input.value = ""; fm.value = value || []; fm.onsubmit = e => e.preventDefault(); fm.input.oninput = function(e) { e.stopPropagation(); if ( optionsSet.has(fm.input.value) && fm.value.indexOf(fm.input.value) === -1 ) { fm.value.push(fm.input.value); renderSelection(); fm.dispatchEvent(new CustomEvent("input")); fm.input.value = ""; } }; renderSelection(); }, form: html` ` }); form.output.style["margin-left"] = "0px"; return form; }35:Tc33,cssStyles=html` `36:[] 2f:{"title":"BUSTED ModelTest analysis result visualization","cells":[{"id":0,"value":"md`# BUSTED ModelTest analysis result visualization`","pinned":false,"hidden":false,"mode":"ojs"},{"id":660,"value":"md`Load a BUSTED[S] JSON result file `","pinned":false,"hidden":false,"mode":"ojs"},{"id":1051,"value":"viewof dataset = Inputs.select(data_sources, {label: \"Dataset\", format: x => x.label, value: data_sources.find(t => t.label === \"Hepatitus D BUSTED[S] JSON\")})","pinned":false,"hidden":false,"mode":"ojs"},{"id":592,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":958,"value":"md`**Table 1. Results summary.** BUSTED with synonymous rate variation ** found evidence (LRT p-value = ${d3.format(\".8f\")(data[\"test results\"][\"p-value\"])} ≤ 0.05) **of gene-wide episodic diversifying selection in the selected test branches of your phylogeny. Therefore, there is evidence that at least one site on at least one test branch has experienced diversifying selection.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":538,"value":"fig1label=md`**Figure 1**. w3 and p3 plots between unconstrained and constrained, take from busteds versus busteds-mh`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1135,"value":"renderTwoDiscreteDistributions (_.filter (d[0], (c)=>c.type == \"Unconstrained model\"), _.filter (d[1], (c)=>c.type == \"Constrained model\"), {\"label\" : {\"chart\" : \"dN/dS\", \"series\" : [\"Unconstrained model\", \"Constrained model\"]}, \"height\" : 200, \"width\": 800, \"scale\" : \"sqrt\", \"margin\": {top: 5, right: 250, bottom: 20, left: 50}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":577,"value":"fig2_label=md`**Figure 2**. Evidence ratio plots`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1379,"value":"fig2=vegalite ({\n width: 800,\n height: 400,\n \"data\": {\"values\": ER_PLOT_DATA },\n \"mark\": {type: \"line\",\n tooltip : true},\n \"encoding\": {\n \"x\": {\"field\": \"site\", \n \"type\": \"quantitative\", \n \"axis\" : {\"grid\" : false, title : \"site\"}},\n \"y\": {\"field\": \"EvidenceRatio\", \n \"scale\": {\"type\": \"linear\"},\n \"type\": \"quantitative\", \n \"axis\" : {\"grid\" : false, title : \"Evidence Ratio value\"}},\n \"stroke\": {\"field\": \"Method\"}\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1394,"value":"fig2a_label=md`**Figure 2a**. Evidence ratio plots (log scaled y)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1392,"value":"fig2a=vegalite ({\n width: 800,\n height: 400,\n \"data\": {\"values\": ER_PLOT_DATA },\n \"mark\": {type: \"line\",\n tooltip : true},\n \"encoding\": {\n \"x\": {\"field\": \"site\", \n \"type\": \"quantitative\", \n \"axis\" : {\"grid\" : false, title : \"site\"}},\n \"y\": {\"field\": \"EvidenceRatio\", \n \"scale\": {\"type\": \"log\"},\n \"type\": \"quantitative\", \n \"axis\" : {\"grid\" : false, title : \"Evidence Ratio value\"}},\n \"stroke\": {\"field\": \"Method\"}\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"html`\n \n

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1352,"value":"## Figure 3 -- SRV Distribution","pinned":false,"hidden":false,"mode":"md"},{"id":1355,"value":"renderTwoDiscreteDistributions_SRV (_.filter (SRV_dist[0], (c)=>c.type == \"Unconstrained model\"), _.filter (SRV_dist[1], (c)=>c.type == \"Constrained model\"), {\"label\" : {\"chart\" : \"dN/dS\", \"series\" : [\"Unconstrained model\", \"Constrained model\"]}, \"height\" : 200, \"width\": 800, \"scale\" : \"sqrt\", \"margin\": {top: 5, right: 250, bottom: 20, left: 50}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs"},{"id":929,"value":"## Declares","pinned":false,"hidden":false,"mode":"md"},{"id":638,"value":"floatFormat = d3.format (\"2g\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"d3 = require (\"d3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":416,"value":"floatFmt = d3.format (\".2g\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":841,"value":"seqNames = (tree)=> {\n let seq_names = [];\n tree.traverse_and_compute (n=>{\n if (n.children && n.children.length) return;\n seq_names.push (n.data.name);\n });\n return seq_names;\n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"_=require(\"lodash\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":711,"value":"totalTreeLength = (tree)=> {\n let L = 0;\n tree.traverse_and_compute ( (n)=> {\n if (tree.branch_length (n)) {\n L += +tree.branch_length (n);\n }\n });\n return L;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1066,"value":"data_sources = [\n {'url' : 'https://raw.githubusercontent.com/aglucaci/BUSTED_ModelTest/main/analysis/HIV_RT.nex.BUSTEDS.json', 'label' : \"HIV RT BUSTED[S] JSON\"},\n {'url' : 'https://raw.githubusercontent.com/aglucaci/BUSTED_ModelTest/main/analysis/HepatitisD.nex.BUSTEDS.json', 'label' : \"Hepatitus D BUSTED[S] JSON\"},\n {'url' : 'https://raw.githubusercontent.com/aglucaci/BUSTED_ModelTest/main/analysis/HepatitisD.nex.BUSTEDS-MH.json', 'label' : \"Hepatitus D BUSTED[S]-MH JSON\"},\n {'url' : 'https://raw.githubusercontent.com/aglucaci/BUSTED_ModelTest/main/analysis/HepatitisD.nex.BUSTED-MH.json', 'label' : \"Hepatitus D BUSTED-MH JSON\"},\n {'url' : 'https://raw.githubusercontent.com/aglucaci/BUSTED_ModelTest/main/analysis/HepatitisD.nex.BUSTED.json', 'label' : \"Hepatitus D BUSTED JSON\"}\n \n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1071,"value":"data = fetch(dataset[\"url\"])\n .then(function(response){\n return response.json();\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1116,"value":"er_values_opt_null = _.chain(data[\"Evidence Ratios\"][\"optimized null\"][0]).toPairs().map ((d)=>{return {'site' : +d[0], 'EvidenceRatio' : d[1], \"Method\": \"Optimized null\", '2_ln_EvidenceRatio' : Math.log(d[1]) * 2}}).value()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1120,"value":"er_values_constrained = _.chain(data[\"Evidence Ratios\"][\"constrained\"][0]).toPairs().map ((d)=>{return {'site' : +d[0], 'EvidenceRatio' : d[1], \"Method\": \"Constrained\", '2_ln_EvidenceRatio' : Math.log(d[1]) * 2}}).value()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1124,"value":"ER_PLOT_DATA = er_values_constrained.concat(er_values_opt_null)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1142,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1369,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":1256,"value":"d1 = {\n const sData = data[\"fits\"][\"Unconstrained model\"][\"Rate Distributions\"][\"Test\"];\n sData[0].type = \"Unconstrained model\";\n sData[0].index = 0;\n sData[1].type = \"Unconstrained model\";\n sData[1].index = 1;\n sData[2].type = \"Unconstrained model\";\n sData[2].index = 2;\n return sData;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1166,"value":"d2 = {\n const sData = data[\"fits\"][\"Constrained model\"][\"Rate Distributions\"][\"Test\"];\n sData[0].type = \"Constrained model\";\n sData[0].index = 0;\n sData[1].type = \"Constrained model\";\n sData[1].index = 1;\n sData[2].type = \"Constrained model\";\n sData[2].index = 2;\n return sData;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1184,"value":"d = Array(d1).concat(Array(d2));","pinned":false,"hidden":false,"mode":"ojs"},{"id":1357,"value":"SRV_d1 = {\n const sData = data[\"fits\"][\"Unconstrained model\"][\"Rate Distributions\"][\"Synonymous site-to-site rates\"];\n sData[0].type = \"Unconstrained model\";\n sData[0].index = 0;\n sData[1].type = \"Unconstrained model\";\n sData[1].index = 1;\n sData[2].type = \"Unconstrained model\";\n sData[2].index = 2;\n return sData;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1359,"value":"SRV_d2 = {\n const sData = data[\"fits\"][\"Constrained model\"][\"Rate Distributions\"][\"Synonymous site-to-site rates\"];\n sData[0].type = \"Constrained model\";\n sData[0].index = 0;\n sData[1].type = \"Constrained model\";\n sData[1].index = 1;\n sData[2].type = \"Constrained model\";\n sData[2].index = 2;\n return sData;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1364,"value":"SRV_dist = Array(SRV_d1).concat(Array(SRV_d2));","pinned":false,"hidden":false,"mode":"ojs"},{"id":933,"value":"## Imports","pinned":false,"hidden":false,"mode":"md"},{"id":350,"value":"import {legend} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":78,"value":"phylotree=require(\"https://dl.dropboxusercontent.com/s/i528j2lqnyzknit/phylotree.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":127,"value":"import { table } from \"@gampleman/table\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":432,"value":"vegalite = require (\"vega-embed\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":174,"value":"import {select, text, input, autoSelect} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":833,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":587,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":598,"value":"simpleIcons = html``","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W36","stdlib":"1","titling":"auto"}