31:T52f,md` 1. ** ID ** : gene / alignment ID 2. ** Sequences ** : number of sequences in the aligment 3. ** Sites ** : number of sites in the alignment 3. ** L (FG) / L (BG) ** : tree length under the unconstrained model (FG branches / BG branches) 4. ** FG q-value ** : q-value (Benjamini-Hochberg) of the BUSTED test on foreground branches; if significant (bolded), implies that there are detectable differences in selection **intensity** between ciliate groups. 5. ** BG q-value ** : q-value of the BUSTED test on background branches; if significant (bolded), implies that there are detectable differences in selection **intensity** between ciliate groups. 6. ** S.sites (FG/BG) ** : Sites that are showing support for positive selection in the Foreground/Background branches with evidence ratio of 100 or higher. 7. ** DIFF q-value ** : q-value of the tests for differences in selection between FG and BG; if significant (bolded), implies that there are detectable differences in selection **regimes**. 8. ** Selection associated with phenotype ** : if Yes, then there is selection on **foreground**, no selection on **background**, and **differences** in selection between the two groups at q ≤ ${critical_value}. 9. **TYPE**: test result pattern (FG/BG/DIFF), 0 for not significant, 1 for significant. `32:T47d,{ let rates = _.groupBy (_.flatten (_.map (_.get (result_json, [gene_id,"distributions","unconstrained","Rate Distributions"]), (d,k)=> { return _.map (d, (r)=>{ let rp = _.clone(r); rp.omega = Math.max (1e-10, rp.omega); rp.type = k; return rp;}); })), (d)=>d.type); delete rates["Synonymous site-to-site rates"]; let rates2 = _.groupBy (_.flatten (_.map (_.get (result_json, [gene_id,"distributions","shared","Rate Distributions"]), (d,k)=> { return _.map (d, (r)=>{ let rp = _.clone(r); rp.omega = Math.max (1e-10, rp.omega); rp.type = k; return rp;}); })), (d)=>d.type); delete rates2["Synonymous site-to-site rates"]; let toPlot = [[],[]]; _.each (rates, (d,k)=> { toPlot [0].push (k); toPlot[1].push (d); }); _.each (rates2, (d,k)=> { toPlot[0].push ("Shared"); toPlot[1].push (d); }); return renderNDiscreteDistributions (toPlot[1],{"label" : {"chart" : "dN/dS", "series" : toPlot[0]}, "height" : 30, "width" : 600, "scale" : "log", "x" : "omega", "w" : "proportion", "margin" : {top: 5, right: 100, bottom: 32, left: 20}}) }33:T8ed,displayed_tree = { let tree = tree_object[0]; var t = tree.render("#tree_container", { //height:1024, width:800, 'show-scale' : true, 'left-right-spacing': 'fit-to-size', //'top-bottom-spacing': 'fit-to-size', //'internal-names' : true, 'is-radial' : false, 'node_circle_size' : (n)=>0 }); const bs = (n) => { if (tree.is_leafnode (n)) { return 3; } return 1; }; let nodeStates = null; t.node_bubble_size = bs; t.phylotree.node_bubble_size = bs; t.options["draw-size-bubbles"] = true; t.font_size = 10; t.spacing_x (10); t.phylotree.branch_length_accessor = n=> { //console.log (summary_json[segment_id]); let bl = tree_object[2][n.data.name]; /*if (bl > 0.25) { n.data.censored_bl = true; return 0.25; } else { n.data.censored_bl = false; }*/ return bl; } t.node_label ((n)=>{ return n.data.name.split ("_").slice (0,3).join (" "); //return ""; }); function sort_nodes (asc) { tree.traverse_and_compute (function (n) { var d = 1; if (n.children && n.children.length) { d += d3.max (n.children, function (d) { return d["count_depth"];}); } n["count_depth"] = d; }); tree.resort_children (function (a,b) { return (a["count_depth"] - b["count_depth"]) * (asc ? 1 : -1); }); } sort_nodes (true); t.style_nodes ((e,n) => { e.selectAll ("title").data ([n.data.name]).join ("title").text ((d)=>d); if (n.data.name in tree_object[1]) { let binfo = tree_object[1][n.data.name]; e.selectAll ("circle").style ('fill', species_colors (binfo)); e.selectAll ("text").style ('fill', species_colors (binfo)); } //} }); t.style_edges ((e,d) => { if (d.target.data.name in tree_object[1]) { let binfo = tree_object[1][d.target.data.name]; console.log (e); e.style ('stroke', species_colors (binfo)); e.style ('stroke-width', 2); } }); t.placenodes(); t.update(); return t; }34:T710,plotPie = (values, id, skipK)=>{ skipK = true; return vegalite ({ "columns": 3, "hconcat": _.map (_.groupBy (values, (d)=>d.type), (d, type) => { let is_dnds = "omega" in d[0]; let title = (is_dnds ? "ω for " : "") + type + (type == baseline_by_segment[id] ? " (reference)" : ""); let rate = is_dnds ? "omega" : "rate"; return { "title" : title, "data" : {"values" : d}, "encoding": { "theta": {"field": "proportion", "type": "quantitative", "stack": true}, "color": {"field": rate, "type": "quantitative", "title" : "ω", "legend" : {"titleFontSize" : 14, "orient" : "top"}, "scale": { "domain" : [0,1,4], "type" : "sqrt", "clamp" : true, "scheme": "sinebow" } }}, "layer" : [ { "mark": {"type": "arc", "innerRadius": 40, "outerRadius" : 60, tooltip : true, padAngle : 0.0, strokeWidth : 1, strokeOpacity: 1}, "encoding" : { "stroke" : {value : "black"}, } }, { "mark": {"type": "text", "outerRadius" : 70, "fontSize" : 18}, "encoding": { "color" : {"value" : "black"}, "text": { "field": rate, "type": "nominal", "format" : ".2f", "condition": {"test": "datum['" + rate +"'] <= 1.", "value": ""}, } } }, { "mark": {"type": "text", "outerRadius" : 20, "fontSize" : 18}, "encoding": { "color" : {"value" : "black"}, "text": { "field": "proportion", "type": "nominal", "format" : ".2p", "condition": {"test": "datum['" + rate +"'] <= 1.", "value": ""} } } } ]} }), "view": {"stroke": null} }) }35:Te07,table_data = { let res = _.map (_.toPairs (result_json), (d)=> { let res = { "ID" : d[0] }; if (d[1].tests) { let pfg = (d)=>d.tests.FG["p-value"]; let pbg = (d)=>d.tests.BG["p-value"]; let pdiff = (d)=>d.tests.DIFF["p-value"]; let prelax = (d)=>_.get (d, ["RELAX","test results", "p-value"]); let haz = (d)=>pfg(d)<=0.05 && pbg (d)>0.05 && pdiff (d)<=0.05; let sites = (d)=>d.fg_selected; let sites_bg = (d)=> d.bg_selected; let l = (d)=>_.mapValues(_.groupBy (_.toPairs(d.lengths), (i)=>d.tested[0][i[0]]), (ll)=>d3.sum (ll, (i)=>i[1]))["test"]; let l_bg = (d)=>_.mapValues(_.groupBy (_.toPairs(d.lengths), (i)=>d.tested[0][i[0]]), (ll)=>d3.sum (ll, (i)=>i[1]))["background"]; let inject = [ ["Sequences", ["sequences"]], ["Sites", ["sites"]], ["FG q-value", pfg], ["BG q-value", pbg], ["DIFF q-value", pdiff], ["S.Sites (FG)", sites], ["S.Sites (BG)", sites_bg], ["L (FG)", l], ["L (BG)", l_bg], ["RELAX q-value", prelax], ["RELAX K", ["RELAX","test results","relaxation or intensification parameter"]], ["ω1", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Test","0","omega"])], ["p1", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Test","0","proportion"])], ["ω2", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Test","1","omega"])], ["p2", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Test","1","proportion"])], ["ω3", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Test","2","omega"])], ["p3", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Test","2","proportion"])], ["ω1 BG", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Background","0","omega"])], ["p1 BG", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Background","0","proportion"])], ["ω2 BG", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Background","1","omega"])], ["p2 BG", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Background","1","proportion"])], ["ω3 BG", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Background","2","omega"])], ["p3 BG", (d)=>_.get (d, ["distributions","unconstrained", "Rate Distributions","Background","2","proportion"])], ]; _.each (inject, (i)=> { res[i[0]] = _.isFunction (i[1]) ? i[1](d[1], d[0]) :_.get (d[1], i[1]); }); } else { res = null; } return res; }); res = _.filter (res, (d)=>d); if (filter.length) { res = _.filter (res, (d)=>d["L (FG)"] < 50 && d["L (BG)"] < 50 && d["p3"] >= 1./(d["Sequences"]*d["Sites"]) && d["p3 BG"] >= 1./(d["Sequences"]*d["Sites"])); } _.each (["FG q-value", "BG q-value", "DIFF q-value","RELAX q-value"], (field)=> { let fdr = computeFDR (_.map (res, (d)=>d[field])); _.each (fdr, (d,i)=> { d[field] = fdr[i][2]; }); }); _.each (res, (rec)=> { rec["PH"] = (rec["FG q-value"] <= critical_value && rec["BG q-value"] > critical_value && rec["DIFF q-value"] <= critical_value); rec["TYPE"] = "C" + (rec["FG q-value"] <= critical_value ? 1 : 0) + (rec["BG q-value"] > critical_value ? 0 : 1) + (rec["DIFF q-value"] <= critical_value ? 1: 0); }); return res; };36:[] 2f:{"title":"Visualizing BUSTED-PH analysis results","cells":[{"id":0,"value":"md`# Visualizing BUSTED-PH analysis results`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3176,"value":"\nviewof phenotype = select ({\n \"options\" : [\"zoonomia-2023\",\"zoonomia-2023-srv\", \"marine\",\"masstop80\", \"marine-2022\", \"mole\", \"marine-no-walrus\",\"marine-zoonomia\",\"marine-zoonomia-srv\",\"marine-zoonomia-filtered\", \"vocal-accelerated\",\"vocal-accelerated-nosrv\",\"vocal-conserved\",\"vocal-conserved-nosrv\", \"vocal-random100\", \"vocal-random100-nosrv\"],\n \"value\" : \"zoonomia-2023\",\n \"title\" : \"Phenotype\"\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":2156,"value":"md`### Summary of BUSTED-PH analyses\nBUSTED-PH results are available for **${table_data.length}** alignments. Of those \n\n* **${_.filter (table_data, (d)=>d[\"FG q-value\"]<=critical_value).length}** had evidence of selection on **Foreground**\n* **${_.filter (table_data, (d)=>d[\"BG q-value\"]<=critical_value).length}** had evidence of selection on **Background**\n* **${_.filter (table_data, (d)=>d[\"DIFF q-value\"]<=critical_value).length}** had evidence of differences between **Foreground** and **Background**\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3267,"value":"viewof search = Inputs.search(table_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":3464,"value":"viewof filter = Inputs.checkbox([\"Filter problematic alignments\"])","pinned":false,"hidden":false,"mode":"ojs"},{"id":2809,"value":"table1_title = md`**Table 1** BUSTED-PH results on individual alignments`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2817,"value":"table1 = Inputs.table(search, {\n rows : 25,\n format: {\n \"FG q-value\": (val)=>val <= critical_value ? html`${d3.format (\".4e\") (val)}` : d3.format (\".4e\") (val),\n \"BG q-value\": (val)=>val <= critical_value ? html`${d3.format (\".4e\") (val)}` : d3.format (\".4e\") (val),\n \"DIFF q-value\": (val)=>val <= critical_value ? html`${d3.format (\".4e\") (val)}` : d3.format (\".4e\") (val),\n \"PH\" : (val)=> val ? \"Yes\" : \"No\",\n \"L (FG)\" : (val) => val > 100 ? html`${d3.format (\".4f\") (val)}` : d3.format (\".4f\") (val),\n \"L (BG)\" : (val) => val > 100 ? html`${d3.format (\".4f\") (val)}` : d3.format (\".4f\") (val) ,\n \"RELAX q-value\": (val)=>val <= critical_value ? html`${d3.format (\".4e\") (val)}` : d3.format (\".4e\") (val),\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2838,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":2912,"value":"fig1_label = md`**Figure 1**. Disributions of mean ω by group`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2920,"value":"fig1=vegalite ({\n \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.json\",\n \"data\": {\n \"values\": _.filter (mean_dnds_plot, (r)=>r.omega < 2)\n },\n \"width\": 800,\n \"height\": 50,\n \"transform\":[{\n \"density\": \"omega\",\n \"groupby\": [\"clade\"],\n \"bandwidth\": 0.025\n }],\n \"mark\": {type: \"area\", \"opacity\" : 0.5, tooltip : true, line : true},\n \"encoding\": {\n \"x\": {\n \"field\": \"value\",\n \"grid\" : null,\n \"title\": \"Density\",\n \"type\": \"quantitative\",\n \"axis\": {\"grid\": false}\n },\n \"y\": {\n \"field\": \"density\",\n \"type\": \"quantitative\",\n \"title\" : \"\",\n \"axis\": {\"grid\": false}\n },\n \"color\" : {\"value\" : \"grey\"},\n \"row\" : {\"field\" : \"clade\", \"title\" : \"dN/dS\", \"sort\": \"ascending\"}\n }\n})\n\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":2943,"value":"table2_label = md`**Table 2**. Disributions of mean ω by group`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2946,"value":"table2 = table (mean_dnds_groups,{\n limit: 5000,\n enableCSVDownload: true,\n sort: true,\n enableFilter: false,\n columns: [\n {\n key : 'group',\n name: \"Group\"\n }, \n {\n key : 'mean',\n name: \"Mean\",\n render: (val)=>float_format (val)\n }, \n {\n key : 'median',\n name: \"Median\",\n render: (val)=>float_format (val)\n }, \n {\n key : 'Q1',\n name: \"5%\",\n render: (val)=>float_format (val)\n },\n {\n key : 'Q3',\n name: \"95%\",\n render: (val)=>float_format (val)\n }\n ]\n})\n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":2992,"value":"md`### Summary of RELAX analyses\nRELAX results are available for **${_.size (_.filter (result_json, (d)=>\"RELAX\" in d))}** alignments. Of those, **${_.filter (table_data, (d)=>d[\"RELAX q-value\"]<=critical_value).length}** yeilded a sigfinicant result (q≤${critical_value}) for differences in selective constraint between branch groups.\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2233,"value":"md`### Gene-by-gene information`","pinned":false,"hidden":false,"mode":"ojs"},{"id":966,"value":"viewof gene_id = {\n const dd3 = autoSelect ({\n title: \"Gene ID\",\n options: _.keys (result_json)\n \n });\n dd3.input.style.fontSize = \"12px\";\n dd3.input.style.marginTop = \"8px\";\n return dd3;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2643,"value":"md`#### Detailed BUSTED-PH results`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2636,"value":"md`\n**${gene_id}** has \n${_.get (result_json,[gene_id,\"sequences\"])} sequences and ${_.get (result_json,[gene_id,\"sites\"])} sites.\n\n_Test summary._\n\n1. The p-value for selection of **foreground** branches **${float_format(_.get (result_json,[gene_id,\"tests\",\"FG\",\"p-value\"]))}**.\n2. The p-value for selection of **background** branches **${float_format(_.get (result_json,[gene_id,\"tests\",\"BG\",\"p-value\"]))}**.\n3. The p-value for differences in selection between the two sets of branches **${float_format(_.get (result_json,[gene_id,\"tests\",\"DIFF\",\"p-value\"]))}**.\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2137,"value":"fig2_label = md`**Figure 2**. Rate distributions for this gene using the BUSTED-PH model`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3302,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":3360,"value":"md`#### Detailed RELAX results\n\n_Test summary._\n\nThe p-value for relaxation/intensification of selection on foreground relative to background branches is **${float_format(_.get (result_json,[gene_id,\"RELAX\",\"test results\",\"p-value\"]))}**, and the relaxation/intensification parameter **K** = **${float_format(_.get (result_json,[gene_id,\"RELAX\",\"test results\",\"relaxation or intensification parameter\"]))}.**\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3372,"value":"fig3_label = md`**Figure 3**. Rate distributions for this gene using the RELAX model`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3374,"value":"{\n let rates = _.groupBy (_.flatten (_.map (_.get (result_json, [gene_id,\"RELAX\",\"distributions\"]), (d,k)=> {\n return _.map (d, (r)=>{\n let rp = _.clone(r);\n rp.omega = Math.max (1e-10, rp.omega);\n rp.type = k;\n return rp;});\n \n })), (d)=>d.type);\n\n\n let toPlot = [[],[]];\n _.each (rates, (d,k)=> {\n toPlot [0].push (k);\n toPlot[1].push (d);\n });\n \n return renderNDiscreteDistributions (toPlot[1],{\"label\" : {\"chart\" : \"dN/dS\", \"series\" : toPlot[0]}, \"height\" : 30, \"width\" : 600, \"scale\" : \"log\", \"x\" : \"omega\", \"w\" : \"proportion\", \"margin\" : {top: 5, right: 100, bottom: 32, left: 20}})\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2236,"value":"md`### Tree for ${gene_id}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1941,"value":"trendLegend = swatches({\n color: species_colors,\n title: \"Viral species\",\n //tickFormat: \"%\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":870,"value":"html`\n \n

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3397,"value":"exportNewick = {\n tree_object[0].branch_length_accessor = (n)=>tree_object[2][n.data.name] ;\n return tree_object[0].get_newick();\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2701,"value":"md`### Libraries and data`","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"d3 = require (\"d3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":11,"value":"phylotree=require (\"https://dl.dropboxusercontent.com/s/i528j2lqnyzknit/phylotree.js\")\n//require (\"phylotree/build/phylotree.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"_=require(\"lodash\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":78,"value":"//resolve(\"phylotree@0.1/phylotree.css\")\n//require (\"https://dl.dropbox.com/s/mjhii51tjy1o5gt/phylotree.js\")\nhtml`\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1905,"value":"tree_object = [new phylotree.phylotree(_.get (result_json, [gene_id,\"tree\"]) || \"()\"), _.get (result_json, [gene_id,\"tested\",0]) || [], _.get (result_json, [gene_id,\"lengths\"])]","pinned":false,"hidden":false,"mode":"ojs"},{"id":127,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":874,"value":"import { table } from \"@gampleman/table\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":174,"value":"import {select,checkbox, autoSelect} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":488,"value":"vegalite = require(\"vega-embed\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":2288,"value":"float_format = d3.format (\".3g\");","pinned":false,"hidden":false,"mode":"ojs"},{"id":2217,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":2321,"value":"report_ratio = (a,b)=> {\n if (a == 0 && b == 0) return 'N.D.';\n if (a == 0) return 'Infinite';\n return float_format (b/a);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1929,"value":"species = new Set(_.flatten(_.map (has_relax, (f)=>_.map (_.uniqBy (_.toPairs (f[\"tested\"][0]), (d)=>d[1]), (d)=>d[1]))))","pinned":false,"hidden":false,"mode":"ojs"},{"id":3030,"value":"has_relax = _.chain (result_json).toPairs().filter ((d)=>\"tested\" in d[1]).fromPairs().value()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1937,"value":"species_colors = d3.scaleOrdinal(d3.schemeCategory10).domain ([...species]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":3228,"value":"critical_value = 0.1","pinned":false,"hidden":false,"mode":"ojs"},{"id":2785,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":3205,"value":"computeFDR = (values)=> {\n const N = values.length;\n return _.chain (values).map ((d,i)=>[i,d]).sortBy (d=>d[1]).map ((d,i)=>[d[0],d[1],Math.min (1,d[1]*(N/(i+1)))]).sortBy (d=>d[0]).value();\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":2475,"value":"baseline_by_segment = _.chain (result_json).toPairs().filter ((d)=>\"fits\" in d[1]).map ((d)=> {\n d[1]=\"Reference\";\n return d;\n}).fromPairs().value();","pinned":false,"hidden":false,"mode":"ojs"},{"id":2952,"value":"mean_dnds_groups = _.chain (_.groupBy (mean_dnds_plot, (d)=>d.clade)).map ((d,k)=>{\n return {\n group : k,\n mean : d3.mean (d, (e)=>e.omega),\n median : d3.median (d, (e)=>e.omega),\n Q1 : d3.quantile (d, 0.05, (e)=>e.omega),\n Q3 : d3.quantile (d, 0.95, (e)=>e.omega)\n };\n}).value()","pinned":false,"hidden":false,"mode":"ojs"},{"id":2904,"value":"mean_dnds_plot = _.filter (_.flatten (_.map (mean_dnds, (d, f)=> {\n return _.map (d, (dnds, gr)=> { \n return {'clade' : gr, \"omega\" : dnds, \"gene\" : f};\n });\n})), (r)=>_.isNumber (r.omega) && r.clade != \"Unclassified\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":2865,"value":"mean_dnds = {\n return _.mapValues (result_json, (d,f)=> {\n if (\"fits\" in d == false) return; \n let test_groups = new Set (_.values (d.tested[0]));\n let mapper = {\"Unclassified\" : \"Unclassified\"};\n if (test_groups.has (\"Test\")) {\n _.some (d.tested[0], (g,s) => {\n if (g == \"Test\") {\n mapper[\"Test\"] = s.split (\"_\")[0]; \n } else {\n mapper[\"Reference\"] = s.split (\"_\")[0]; \n }\n return _.size (mapper) == 3;\n }\n );\n } else {\n mapper = _.fromPairs ( _.map ([...test_groups], (d)=>[d,d]));\n }\n return _.fromPairs ([['mapping', mapper]].concat(_.map ([...test_groups], (g)=> {\n return ([mapper[g],d.fits[\"MG94xREV with separate rates for branch sets\"][\"Rate Distributions\"][\"non-synonymous/synonymous rate ratio for *\" + g + \"*\"][0][0]]);\n })));\n })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":754,"value":"result_json = await d3.json (\"https://data.hyphy.org/web/busted-ph/\"+phenotype+\".json\");","pinned":false,"hidden":false,"mode":"ojs"},{"id":3450,"value":"_.filter (table_data, (d)=>d[\"RELAX q-value\"] <= 0.1 && d[\"RELAX K\"] > 1).length","pinned":false,"hidden":false,"mode":"ojs"},{"id":1943,"value":"import { legend, swatches } from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":2060,"value":"import {translation_table} from \"@spond/usual-vs-unusual-mutation-analyses\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":3299,"value":"import {renderNDiscreteDistributions} from \"@spond/omega-plots\"","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W36","stdlib":"1","titling":"auto"}