2f: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; }30:T524,interpretation = { let inter = "" if (chosen_json['tests']['FG']['p-value'] > 0.05){ inter = "There is no evidence of this gene experiencing positive selection associated with the foreground (test) branches." } else { if (chosen_json['tests']['BG']['p-value'] > 0.05) { if (chosen_json['tests']['DIFF']['p-value'] > 0.05) { inter = "There is evidence of this gene experiencing positive selection associated with the foreground (test) branches, but there is no statistically significant difference between the test and background branches in terms of selective pressure." } else { inter = "There is strong evidence of this gene experiencing positive selection associated with the foreground (test) branches." } } else { inter = "For this gene, selection is acting on the foreground (test) branches, but selection is also acting on background branches. " if (chosen_json['tests']['DIFF']['p-value'] > 0.05) { inter = inter + "There is no statistically significant difference between the test and background branches in terms of selective pressure." } else { inter = inter + "There is a statistically significant difference between the test and background branches in terms of selective pressure." } } } return inter }31:T5d1,table_data = { let for_table = [] for (const key in bph_results_json ) { const obj = { "ID" : key, "Sequences" : bph_results_json[key]['sequences'], "Sites" : bph_results_json[key]['sites'], "Num_FG" : Object.values(bph_results_json[key]['tested'][0]).filter(val => val === "test").length, "FG_pval" : bph_results_json[key]['tests']['FG']['p-value'], "BG_pval" : bph_results_json[key]['tests']['BG']['p-value'], "DF_pval" : bph_results_json[key]['tests']['DIFF']['p-value'], "ω1" : bph_results_json[key]['distributions']['unconstrained']['Rate Distributions']['Test'][0]['omega'], "p1" : bph_results_json[key]['distributions']['unconstrained']['Rate Distributions']['Test'][0]['proportion'], "ω2" : bph_results_json[key]['distributions']['unconstrained']['Rate Distributions']['Test'][1]['omega'], "p2" : bph_results_json[key]['distributions']['unconstrained']['Rate Distributions']['Test'][1]['proportion'], "ω3" : bph_results_json[key]['distributions']['unconstrained']['Rate Distributions']['Test'][2]['omega'], "p3" : bph_results_json[key]['distributions']['unconstrained']['Rate Distributions']['Test'][2]['proportion'], "Class" : "C" + (bph_results_json[key]['tests']['FG']['p-value'] <= 0.05 ? 1 : 0) + (bph_results_json[key]['tests']['BG']['p-value'] > 0.05 ? 0 : 1) + (bph_results_json[key]['tests']['DIFF']['p-value'] <= 0.05 ? 1: 0) } for_table.push(obj) } return for_table }32:[{"id":"e5734a9b51641e2246e16b6796f7102319171b46b9c0ea352851af206ca7e06942c8f7e9774ae14eb55b709f9a636801ae37cf4f69d39c28c8699bf18dec478b","href":"https://static.observableusercontent.com/files/e5734a9b51641e2246e16b6796f7102319171b46b9c0ea352851af206ca7e06942c8f7e9774ae14eb55b709f9a636801ae37cf4f69d39c28c8699bf18dec478b","name":"prelim-10312023.json","type":"application/json","lastModified":1698791680883.417,"size":27801461}] 2d:{"title":"BUSTED-PH: upload a combined json file to visualize (Added Preliminary Endothermy Results)","cells":[{"id":0,"value":"# BUSTED-PH: upload a combined json file to visualize (Added Preliminary Endothermy Results)","pinned":false,"hidden":false,"mode":"md"},{"id":221,"value":"**Upload a json file that contains the output of multiple BUSTED-PH json files using combine_results.py.** We recommend that before combining the results, the name of the json file indicates the name of the gene/alignment.","pinned":false,"hidden":false,"mode":"md"},{"id":15,"value":"viewof bph_results = params.get (\"url\") ? localFileInput({accept: \".json\", value : params.get (\"url\"), disable: true}) : localFileInput({accept: \".json\"}) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":290,"value":"viewof search = Inputs.search(table_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":294,"value":"table1 = Inputs.table(search, {\n rows : 15\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":298,"value":"\n** Table 1. **\nColumn definitions are as follows: \n1. **ID** the candidate gene/alignment under study,\n2. **Sequences** the number of sequences in the alignment,\n3. **Sites** the number of codons in the alignment \n4. **Num_FG** the number of foreground (i.e. Test) species and ancestral nodes in the alignment, \n5. **FG_pval** the LRT p-value for the test for positive selection in the foreground (test) species, \n6. **BG_pval** the LRT p-value for the test for positive selection in the background species, \n7. **DF_pval** the LRT p-value for the test for the difference between the two selective regimes,\n8. **Class** the significance of p values (FG_pval, BG_pval, and DF_pval respectively) where 1 indicates significance and 0 indicates non-significance at a threshold of 0.05 (table 2).\n","pinned":false,"hidden":false,"mode":"md"},{"id":303,"value":"Class | Interpretation \n-------- | -------- \nC000 | No selection on FG, no selection on BG, no difference between FG and BG selective regimes \nC100 | Selection on FG, no selection on BG, no difference between FG and BG selective regimes\nC010 | No selection on FG, selection on BG, no difference between FG and BG selective regimes\nC001 | No selection on FG, no selection on BG, statistically significant difference between FG and BG selective regimes\nC101 | Selection on FG, no selection on BG, statistically significant difference between FG and BG selective regimes\nC110 | Selection on FG, selection on BG, no difference between FG and BG selective regimes\nC011 | No selection on FG, selection on BG, statistically significant difference between FG and BG selective regimes\nC111 | Selection on FG, selection on BG, statistically significant difference between FG and BG selective regimes","pinned":false,"hidden":false,"mode":"md"},{"id":305,"value":"**Table 2.** Interpretation of class values from table 1. ","pinned":false,"hidden":false,"mode":"md"},{"id":308,"value":"## Exploring individual genes","pinned":false,"hidden":false,"mode":"md"},{"id":223,"value":"viewof gene_id = Inputs.select(Object.keys(bph_results_json), {label: \"Show this gene:\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"trendLegend = swatches({\n color: species_colors\n //tickFormat: \"%\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":48,"value":"html`\n \n

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":178,"value":"\n** Figure 1. **\nGene tree for ${gene_id} generated by BUSTED-PH. Colors indicate foreground, background, and nuisance branches (if using).\n","pinned":false,"hidden":false,"mode":"md"},{"id":101,"value":"## Interpretation of test for positive selection","pinned":false,"hidden":false,"mode":"md"},{"id":104,"value":"1. The p-value for the test for positive selection in the *test* (foreground) branches is: ** ${chosen_json['tests']['FG']['p-value'].toFixed(3)} **\n\n2. The p-value for the test for positive selection in the *background* branches is: ** ${chosen_json['tests']['BG']['p-value'].toFixed(3)} **\n\n3. The p-value for the test for the *difference between* the test (foreground) and background branch sets is: ** ${chosen_json['tests']['DIFF']['p-value'].toFixed(3)} **","pinned":false,"hidden":false,"mode":"md"},{"id":116,"value":"** ${interpretation} **","pinned":false,"hidden":false,"mode":"md"},{"id":121,"value":"## Omega values and their proportions","pinned":false,"hidden":false,"mode":"md"},{"id":126,"value":"omega_plot.legend(\"color\", {\n label: \"Omega values →\",\n tickSize: 3,\n ticks: 10,\n //tickLabelRotate: 45,\n //tickFormat: r.tickFormat,\n //round: r.round,\n width: 600,\n height: 45\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":129,"value":"omega_plot = Plot.plot({\n color: {\n type: \"sqrt\",\n //pivot: 4,\n scheme: \"brbg\",\n reverse: true,\n //legend: true\n }, \n y: {\n domain: ['FG', 'BG', 'ALL']\n },\n marks: [\n Plot.barX(stacked_omegas, {y: \"dist\",x: \"proportion\", fill: 'omega', title: (d) =>\n `${d.dist} omega bin #${d.omega_bin}\\n Omega value: ${d.omega},\\nProportion: ${d.proportion}` }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":170,"value":"\n** Figure 2. **\nOmega distribution for ${gene_id}. Sites were categorized into three omega values for each of the three distributions. The three distributions include: foreground branches, background branches, and all branches (in both FG and BG). Prop indicates proportion of sites that fall into the omega category. The largest omega value category for each of the three distributions are: ${omega_vals[2].toFixed(3)} for the FG, ${omega_vals[5].toFixed(3)} for the BG, and ${omega_vals[8].toFixed(3)} for all branches. \n","pinned":false,"hidden":false,"mode":"md"},{"id":44,"value":"### Parsing Data","pinned":false,"hidden":false,"mode":"md"},{"id":239,"value":"chosen_json = bph_results_json[gene_id]","pinned":false,"hidden":false,"mode":"ojs"},{"id":32,"value":"bph_results_json = await get_json (params.get (\"url\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":26,"value":"get_json = async (json_source)=> {\n if (json_source) {\n return d3.json (json_source);\n }\n return bph_results.json();\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":53,"value":"species_colors = d3.scaleOrdinal(d3.schemeCategory10).domain ([...species]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":56,"value":"species = _.uniq(_.map(chosen_json['tested'][0])).sort()","pinned":false,"hidden":false,"mode":"ojs"},{"id":68,"value":"tree_object = [new phylotree.phylotree(chosen_json['tree'] || \"()\"), chosen_json['tested'][0] || [], chosen_json['lengths']]","pinned":false,"hidden":false,"mode":"ojs"},{"id":97,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":108,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":132,"value":"stacked_omegas = {\n\n let test = chosen_json['distributions']['unconstrained']['Rate Distributions']['Test']\n //return test\n let count = 1\n for (const key in test) {\n test[key]['dist'] = 'FG';\n test[key]['omega_bin'] = count;\n count++\n}\n\n//return test\n let bg = chosen_json['distributions']['unconstrained']['Rate Distributions']['Background']\n count = 1\n for (const key in bg) {\n bg[key]['dist'] = 'BG';\n bg[key]['omega_bin'] = count;\n count++\n}\n let shared = chosen_json['distributions']['shared']['Rate Distributions']['Test']\n count = 1\n for (const key in shared) {\n shared[key]['dist'] = 'ALL';\n shared[key]['omega_bin'] = count;\n count++\n}\n \nconst stacked = [\n ...Object.values(test),\n ...Object.values(bg),\n ...Object.values(shared)\n]; \n return stacked\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":173,"value":"omega_vals =_.map(stacked_omegas, d => d.omega)","pinned":false,"hidden":false,"mode":"ojs"},{"id":270,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":38,"value":"### Imports","pinned":false,"hidden":false,"mode":"md"},{"id":7,"value":"import {file} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":20,"value":"import {localFileInput} from \"@mbostock/localfile\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":23,"value":"params = new URLSearchParams(location.search)","pinned":false,"hidden":false,"mode":"ojs"},{"id":62,"value":"import { Legend, swatches } from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":91,"value":"phylotree=require (\"https://dl.dropboxusercontent.com/s/i528j2lqnyzknit/phylotree.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":153,"value":"import {Plot} from \"@mkfreeman/plot-tooltip\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":323,"value":"import { py, pyodide } from '@gnestor/pyodide'","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}