30:T9cb,plot_data = _.map(C1x1_E, d => { return { 'Gene': d.ID, 'FG_omega1': Number(d['BUSTED-FG omegas'].split(',')[0]), 'FG_omega2': Number(d['BUSTED-FG omegas'].split(',')[1]), 'FG_omega3': Number(d['BUSTED-FG omegas'].split(',')[2]), 'FG_weight1': Number(d['BUSTED-FG proportions'].split(',')[0]), 'FG_weight2': Number(d['BUSTED-FG proportions'].split(',')[1]), 'FG_weight3': Number(d['BUSTED-FG proportions'].split(',')[2]), 'FG_E_omega1': Number(d['BUSTED-FG-E omegas'].split(',')[1]), 'FG_E_omega2': Number(d['BUSTED-FG-E omegas'].split(',')[2]), 'FG_E_omega3': Number(d['BUSTED-FG-E omegas'].split(',')[3]), 'FG_E_omegaE': Number(d['BUSTED-FG-E omegas'].split(',')[0]), 'FG_E_weight1': Number(d['BUSTED-FG-E proportions'].split(',')[1]), 'FG_E_weight2': Number(d['BUSTED-FG-E proportions'].split(',')[2]), 'FG_E_weight3': Number(d['BUSTED-FG-E proportions'].split(',')[3]), 'FG_E_weightE': Number(d['BUSTED-FG-E proportions'].split(',')[0]), 'BG_omega1': Number(d['BUSTED-BG omegas'].split(',')[0]), 'BG_omega2': Number(d['BUSTED-BG omegas'].split(',')[1]), 'BG_omega3': Number(d['BUSTED-BG omegas'].split(',')[2]), 'BG_weight1': Number(d['BUSTED-BG proportions'].split(',')[0]), 'BG_weight2': Number(d['BUSTED-BG proportions'].split(',')[1]), 'BG_weight3': Number(d['BUSTED-BG proportions'].split(',')[2]), 'BG_E_omega1': Number(d['BUSTED-BG-E omegas'].split(',')[1]), 'BG_E_omega2': Number(d['BUSTED-BG-E omegas'].split(',')[2]), 'BG_E_omega3': Number(d['BUSTED-BG-E omegas'].split(',')[3]), 'BG_E_omegaE': Number(d['BUSTED-BG-E omegas'].split(',')[0]), 'BG_E_weight1': Number(d['BUSTED-BG-E proportions'].split(',')[1]), 'BG_E_weight2': Number(d['BUSTED-BG-E proportions'].split(',')[2]), 'BG_E_weight3': Number(d['BUSTED-BG-E proportions'].split(',')[3]), 'BG_E_weightE': Number(d['BUSTED-BG-E proportions'].split(',')[0]), 'delta_omega3_E' : Number(d['BUSTED-FG-E omegas'].split(',')[3]) - Number(d['BUSTED-BG-E omegas'].split(',')[3]), 'delta_omega3' : Number(d['BUSTED-FG omegas'].split(',')[2]) - Number(d['BUSTED-BG omegas'].split(',')[2]), 'delta_weight3' : Number(d['BUSTED-FG proportions'].split(',')[2]) - Number(d['BUSTED-BG omegas'].split(',')[2]), 'delta_weight3_E' : Number(d['BUSTED-FG-E proportions'].split(',')[3]) - Number(d['BUSTED-BG-E proportions'].split(',')[3]) }; });31:T534,viewof detection_plot = { let xvar = selected_branches + '_pval_E' let yvar = selected_branches +'_pval' return Plot.plot({ round: true, height: 330, width : 450, marginTop: 30, marginBottom: 40, marginLeft: 50, paddingBottom : 10, x: {type: "log", "tickFormat" : "2f", "domain" : [1e-8,0.5], "clamp" : true, 'label' : xvar }, y: {type: "log", "tickFormat" : "2f", "domain" : [1e-8,0.5], "clamp" : true, 'label' : yvar }, marks: [ Plot.dot(table_data, {"x": xvar, "y" : yvar, "opacity" : 0.5, "fill" : "darkgrey", channels : {Gene: 'ID'}, tip: true}), Plot.dot(table_data, Plot.pointer({x: xvar, y: yvar, fill: "dodgerblue"})), Plot.text ([ {"x" : 0.0000001, "y": 0.0000001, "t" : _.filter (table_data, (d)=>d[xvar] <= pvcut && d[yvar] <= pvcut).length}, {"x" : 0.0000001, "y": 0.1, "t" : _.filter (table_data, (d)=>d[xvar] <= pvcut && d[yvar] > pvcut).length}, {"y" : 0.0000001, "x": 0.15, "t" : _.filter (table_data, (d)=>d[xvar] > pvcut && d[yvar] <= pvcut).length}, {"y" : 0.1, "x": 0.15, "t" : _.filter (table_data, (d)=>d[xvar] > pvcut && d[yvar] > pvcut).length} ], {"x" : "x", "y" : "y", "text" : "t", "fontSize" : 14, "fill" : "firebrick"}), Plot.ruleY([pvcut]), Plot.ruleX([pvcut]), Plot.ruleY([0]) ] }) }32:T422,get2x2 = (data, branches, pv, key1, key2)=> { let counts = [[0,0],[0,0]]; let busted = 'BUSTED_' + branches let busted_e = 'BUSTED-E_' + branches let p = pv || 0.05; key1 = key1 || "p"; key2 = key2 || "p_e"; _.each (data, (d)=> { counts [d[key1] <= p ? 1 : 0][d[key2] <= p ? 1 : 0] += 1; }); return [ {[busted] : 'No', [busted_e] : 'No', 'Count' : counts[0][0], 'p' : counts[0][0] / data.length * 100.}, {[busted] : 'Yes', [busted_e] : 'No', 'Count' : counts[1][0], 'p' : counts[1][0] / data.length * 100.}, {[busted] : 'No', [busted_e] : 'Yes', 'Count' : counts[0][1], 'p' : counts[0][1] / data.length * 100.}, {[busted] : 'Yes', [busted_e] : 'Yes', 'Count' : counts[1][1], 'p' : counts[1][1] / data.length * 100.}, {[busted] : 'Yes', [busted_e] : '*', 'Count' : counts[1][1] + counts[1][0], 'p' : (counts[1][1] + counts[1][0]) / data.length * 100.}, {[busted] : '*', [busted_e] : 'Yes', 'Count' : counts[0][1] + counts[1][1], 'p' : (counts[1][1] + counts[0][1]) / data.length * 100.}, ]; }33:Tad0,table_data = { function get_omegas(entry, MODEL, OMEGA) { let omegas = [ entry[MODEL]?.fits?.['Unconstrained model']?.['Rate Distributions']?.['Test']?.[0]?.[OMEGA], entry[MODEL]?.fits?.['Unconstrained model']?.['Rate Distributions']?.['Test']?.[1]?.[OMEGA], entry[MODEL]?.fits?.['Unconstrained model']?.['Rate Distributions']?.['Test']?.[2]?.[OMEGA] ]; if (MODEL.includes('-E')) { omegas.push(entry[MODEL]?.fits?.['Unconstrained model']?.['Rate Distributions']?.['Test']?.[3]?.[OMEGA]); } return omegas.join(','); } function getGeneNameByProtId(prot_id) { const result = ensembl_convert.find(obj => obj.prot_id === prot_id); return result ? result.gene_name : prot_id; } let res = _.map (result_json, (val, key)=> { if ('BUSTED-PH-E'in val && 'BUSTED-FG' in val && 'BUSTED-PH' in val){ return { "ID" : dataset != 'rodent_busted-phe.json' ? key: getGeneNameByProtId(key), //"Class" : (val['BUSTED-PH']['FG p-val'] < 0.05 ? '1' : '0') + (val['BUSTED-PH']['BG p-val'] < 0.05 ? '1' : '0') + (val['BUSTED-DF']['FG p-val'] < 0.05 ? '1' : '0'), "FG_pval_E" : val['BUSTED-PH-E']['FG p-val'], "BG_pval_E" : val['BUSTED-PH-E']['BG p-val'], "DF_pval_E" : val['BUSTED-PH-E']['DF p-val'], "FG_pval" : val['BUSTED-PH']['FG p-val'], "BG_pval" : val['BUSTED-PH']['BG p-val'], "DF_pval" : val['BUSTED-PH']['DF p-val'], "FG_lrt_E" : val['BUSTED-PH-E']['FG LRT'], "BG_lrt_E" : val['BUSTED-PH-E']['BG LRT'], "DF_lrt_E" : val['BUSTED-PH-E']['DF LRT'], "FG_lrt" : val['BUSTED-PH']['FG LRT'], "BG_lrt" : val['BUSTED-PH']['BG LRT'], "DF_lrt" : val['BUSTED-PH']['DF LRT'], 'BUSTED-FG omegas' : get_omegas(val, 'BUSTED-FG', 'omega'), 'BUSTED-BG omegas' : get_omegas(val, 'BUSTED-BG', 'omega'), 'BUSTED-BOTH omegas' : get_omegas(val, 'BUSTED-BOTH', 'omega'), 'BUSTED-FG-E omegas' : get_omegas(val, 'BUSTED-FG-E', 'omega'), 'BUSTED-BG-E omegas' : get_omegas(val, 'BUSTED-BG-E', 'omega'), 'BUSTED-BOTH-E omegas' : get_omegas(val, 'BUSTED-BOTH-E', 'omega'), 'BUSTED-FG proportions' : get_omegas(val, 'BUSTED-FG', 'proportion'), 'BUSTED-BG proportions' : get_omegas(val, 'BUSTED-BG', 'proportion'), 'BUSTED-BOTH proportions' : get_omegas(val, 'BUSTED-BOTH', 'proportion'), 'BUSTED-FG-E proportions' : get_omegas(val, 'BUSTED-FG-E', 'proportion'), 'BUSTED-BG-E proportions' : get_omegas(val, 'BUSTED-BG-E', 'proportion'), 'BUSTED-BOTH-E proportions' : get_omegas(val, 'BUSTED-BOTH-E', 'proportion'), }; } else { return NaN } //else return NaN }) let res_filter = _.filter(res, item => !Number.isNaN(item)) return res_filter }34:T7f9,// FG species for rodent testes: // "Maxomys_surifer_JAE3632", "Maxomys_musschenbroekii_sample1", "Chiropodomys_gliroides_Z25153", "Leopoldomys_sabanus_Z25191", "Chrotomys_whiteheadi_KU168311", "Aethomys_hindei_MVZ196257", "Apodemus_sylvaticus_SMG3823", "Berylmys_bowersi_ABTC116431", "Paucidentomys_vermidax_Z21914", "Tateomys_macrocercus_Z21834", "Sommeromys_macrorhinos_Z21740", "Rhabdomys_pumilio_MNHN1995065", "Dasymys_incomtus_LSUMZ37702", "Waiomys_mamasae_Z20624", "Gracilimus_radix_Z08508", "Anisomys_imitator_ABTC45107", "Mastomys_natalensis_T4162", "Praomys_jacksoni_REC31", "Mus_minutoides_10460X2", "Sundamys_muelleri_JAE1283", "Lorentzimys_nouhuysi_ABTC-46314", "Mus_caroli_10460X9", "Mus_musculus-musculus_10460X14", "Hydromys_chrysogaster_Z5248", "Abeomelomys_sevia_KUM161018", "Mallomys_rothschildi_ABTC47402", "Xenuromys_barbatus_ABTC129204", "Mammelomys_lanosus_ABTC47208", "Chiruromys_vates_ABTC43096 ", "Rattus_exulans_sample1", "Rattus_leucopus_sample1", "Bunomys_chrysocomus_JAE4867", "Bunomys_andrewsi_sample1", "Leptomys_elegans_ABTC45741 ", "Xeromys_myoides_ABTC30709", "Pogonomys_macrourus_ABTC43144", "rnor6", "Rattus_lutreolus_sample2", "Melomys_rufescens_ABTC44798", "Uromys_caudimaculatus_DT10Uc01", "Leporillus_conditor_ABTC13335", "Rattus_hoffmanni_LSUMZ39187", "Rattus_argentiventer_LSUMZ38199", "Rattus_tunneyi_RAT130", "Zyzomys_woodwardi_WAMM21724", "Zyzomys_argurus_ABTC61630", "Zyzomys_maini_ABTC07900", "Leggadina_lakedownensis_WAMM21623", "Leggadina_forresti_WAMM62323", "Conilurus_penicillatus_M14056", "Rattus_colletti_RAT25", "Rattus_villosissimus_sample1", "Notomys_cervinus_M22857", "Mesembriomys_macrurus_ABTC7337", "Mesembriomys_gouldii_ABTC7449", "Pseudomys_fumeus_ABTC08168 ", "Pseudomys_nanus_U1448", "Pseudomys_gracilicaudatus_ABTC08163", "Pseudomys_apodemoides_M16672", "Pseudomys_albocinereus_WAMM18855", "Pseudomys_oralis_RAT7", "Pseudomys_australis_M25541 ", "Pseudomys_desertor_ABTC41464", "Mastacomys_fuscus_M13957", "Pseudomys_higginsi_UC1421", "Pseudomys_hermannsburgensis_ABTC0806735:[{"id":"93f1ee59c0f6ae3943eb0a6ab8a16f3a7001ce61336196e41c9730b9286b9775d6347c120ebb84bcea69b3f26714542a1e21e45dbbb89eabdf3c2cd530bb15f9","href":"https://static.observableusercontent.com/files/93f1ee59c0f6ae3943eb0a6ab8a16f3a7001ce61336196e41c9730b9286b9775d6347c120ebb84bcea69b3f26714542a1e21e45dbbb89eabdf3c2cd530bb15f9","name":"all_genes.csv","type":"text/csv","lastModified":1734720821957.69,"size":5538521}] 2e:{"title":"BUSTED-PHE","cells":[{"id":0,"value":"# BUSTED-PHE","pinned":false,"hidden":false,"mode":"md"},{"id":420,"value":"viewof dataset = Inputs.select(new Map([[\"Mammals, marine\", \"results-lrt.json\"], [\"Rodents, testes size\", \"rodent_busted-phe.json\"], [\"Pollock dataset\", 'combined_pollock.json']]), {value: \"results-lrt.json\", label: \"Choose a dataset and phenotype\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":52,"value":"viewof search = Inputs.search(table_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":55,"value":"table1 = Inputs.table(search, {\n rows : 15\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":500,"value":"## Looking at genes with phenotype-specific positive selection (FG significant, BG no selection, significant difference)","pinned":false,"hidden":false,"mode":"md"},{"id":518,"value":"Inputs.table(pheno_specific_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":505,"value":"pheno_specific_data = {\n let tests = ['_E', '']\n return _.map (tests, (test)=> {\n return {\n 'Test' : test === '_E' ? 'With error correction' : 'No error correction' ,\n 'Pos Sel in FG (C1**)' : _.filter (table_data, (d)=>d['FG_pval' + test] <= 0.05 ).length,\n 'Pos Sel in BG (C*1*)' : _.filter (table_data, (d)=>d['BG_pval' + test] <= 0.05 ).length,\n 'Sig DF (C**1)' : _.filter (table_data, (d)=>d['DF_pval' + test] <= 0.05 ).length,\n 'C101' : _.filter (table_data, (d)=>d['FG_pval' + test] <= 0.05 && d['BG_pval' + test] <= 0.05 && d['DF_pval' + test] <=0.05).length,\n 'C1*1' : _.filter (table_data, (d)=>d['FG_pval' + test] <= 0.05 && d['DF_pval' + test] <=0.05).length, \n };\n });\n\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":393,"value":"C101_E = _.filter(table_data, (v,k) => v.FG_pval_E < pvcut && v.BG_pval_E > pvcut && v.DF_pval_E < pvcut)","pinned":false,"hidden":false,"mode":"ojs"},{"id":397,"value":"C101_noE = _.filter(table_data, (v,k) => v.FG_pval < pvcut && v.BG_pval > pvcut && v.DF_pval < pvcut)","pinned":false,"hidden":false,"mode":"ojs"},{"id":440,"value":"C1x1_E = _.filter(table_data, (v,k) => v.FG_pval_E < pvcut && v.DF_pval_E < pvcut)","pinned":false,"hidden":false,"mode":"ojs"},{"id":444,"value":"C1x1_noE = _.filter(table_data, (v,k) => v.FG_pval < pvcut && v.DF_pval < pvcut)","pinned":false,"hidden":false,"mode":"ojs"},{"id":536,"value":"### Examining C1*1 genes -> is positive selection in background less than foreground? ","pinned":false,"hidden":false,"mode":"md"},{"id":545,"value":"viewof colors = Inputs.select ([\"turbo\", \"brbg\", \"prgn\", \"piyg\", \"puor\", \"rdbu\", \"rdgy\", \"rdylgn\", 'cividis', 'bugn', 'bupu', 'gnbu', 'orrd', 'pubu', 'purd', 'rdpu', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd', 'magma'])","pinned":false,"hidden":false,"mode":"ojs"},{"id":549,"value":"viewof plot_model = Inputs.select ([\"BUSTED\", \"BUSTED-E\"], {\"label\" : \"Model to plot\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":657,"value":"omega_shift = {\nreturn Plot.plot({\n marginTop: 20,\n marginRight: 20,\n marginBottom: 30,\n marginLeft: 50,\n y: {type: \"log\", \"tickFormat\" : \"2f\", \"domain\" : [1,1e5], \"clamp\" : true,},\n grid: true,\n marks: [\n Plot.barY(plot_data, {x: \"Gene\", y: \"delta_omega3_E\", fill: \"forestgreen\", channels : {Gene: 'Gene', FG_E_omega3 : 'FG_E_omega3', BG_E_omega3 : 'BG_E_omega3'}, tip: true}),\n Plot.barY(plot_data, {x: \"Gene\", y: d => -d.delta_omega3_E, fill: \"orange\"}),\n Plot.frame()\n ]\n})\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":690,"value":"weight_shift = {\nreturn Plot.plot({\n marginTop: 20,\n marginRight: 20,\n marginBottom: 30,\n marginLeft: 50,\n y: {type: \"log\", \"tickFormat\" : \"2f\", \"domain\" : [1e-8,1], \"clamp\" : true,},\n grid: true,\n marks: [\n Plot.barY(_.filter(plot_data, d=> d['delta_omega3_E'] < 0), {x: \"Gene\", y: \"delta_weight3_E\", fill: \"forestgreen\", channels : {Gene: 'Gene', FG_E_weight3 : 'FG_E_weight3', BG_E_weight3 : 'BG_E_weight3'}, tip: true}),\n Plot.barY(_.filter(plot_data, d=> d['delta_omega3_E'] < 0), {x: \"Gene\", y: d => -d.delta_weight3_E, fill: \"orange\"}),\n Plot.frame()\n ]\n})\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":552,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":387,"value":"## Comparing selection detection in specific branch sets- before and after error filtering ","pinned":false,"hidden":false,"mode":"md"},{"id":65,"value":"viewof selected_branches = Inputs.select(new Map([[\"FOREGROUND\", \"FG\"], [\"BACKGROUND\", \"BG\"], [\"DIFFERENCE\", \"DF\"],]), {value: \"FG\", label: \"Choose a set of branches\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":363,"value":"Inputs.table(get2x2 (search, selected_branches, pvcut, selected_branches+'_pval', selected_branches+'_pval_E'))","pinned":false,"hidden":false,"mode":"ojs"},{"id":60,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":118,"value":"## Individual gene results","pinned":false,"hidden":false,"mode":"md"},{"id":138,"value":"viewof filter_branches = {\n return Inputs.checkbox(\n new Map([[\"Positive selection FG branches\", 'FG'], [\"Positive selection on BG branches\", 'BG'], [\"Positive selection on all branches\", 'DF']]),\n {label: \"Find genes with\"}\n)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":156,"value":"viewof filter_error = Inputs.radio(new Map([[\"No error filtering\", '_pval'], [\"Error filtering\", '_pval_E']]), {label: \"Find genes with\", value: '_pval_E'})","pinned":false,"hidden":false,"mode":"ojs"},{"id":123,"value":"viewof gene = {\n let filtering = _.map(filter_branches, d=> d + filter_error)\n let genes_to_search = _.map(\n _.filter(search, d => \n filtering.length === 0 || // No filtering if filter_branches is empty\n filtering.every(branch => d[branch] <= 0.05) // Check all branches\n ),\n d => d.ID\n)\n return Inputs.select(genes_to_search, {label: \"Show this gene: (searching from \" + String(genes_to_search.length) + ' genes)'})\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":215,"value":"### Results for selected gene","pinned":false,"hidden":false,"mode":"md"},{"id":223,"value":"P-values for selected gene ${gene}:","pinned":false,"hidden":false,"mode":"md"},{"id":251,"value":"Inputs.table(pval_table)","pinned":false,"hidden":false,"mode":"ojs"},{"id":239,"value":"Omega values for selected gene ${gene}:","pinned":false,"hidden":false,"mode":"md"},{"id":300,"value":"Inputs.table(omega_table)","pinned":false,"hidden":false,"mode":"ojs"},{"id":209,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":361,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":254,"value":"pval_table = _.map(_.filter(table_data, d => d.ID === gene), d => {\n const suffixes = ['_pval', '_pval_E'];\n let test = {'_pval' : 'No error filtering', '_pval_E' : 'Error filtering'}\n return suffixes.map(suffix => ({\n 'Test': test[suffix],\n 'FG': d[`FG${suffix}`],\n 'BG': d[`BG${suffix}`],\n 'DF': d[`DF${suffix}`]\n }))\n})[0]","pinned":false,"hidden":false,"mode":"ojs"},{"id":276,"value":"omega_table = _.map(_.filter(table_data, d => d.ID === gene), d => {\n const tests = _.filter(Object.keys(result_json[gene]), v => !v.includes('PH'));\n \n return tests.map(test => {\n // Split the omega string into an array\n const omegas = d[`${test} omegas`].split(',');\n\n return {\n ['Test']: test,\n 'Omega 1': omegas.length===4 ? Number(omegas[1]).toFixed(3) : Number(omegas[0]).toFixed(3), // Add comma if there's a value\n 'Omega 2': omegas.length===4 ? Number(omegas[2]).toFixed(3) : Number(omegas[1]).toFixed(3),\n 'Omega 3': omegas.length===4 ? Number(omegas[3]).toFixed(3) : Number(omegas[2]).toFixed(3),\n 'Omega E': omegas.length===4 ? Number(omegas[0]).toFixed(3) : ''\n };\n });\n})[0];","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"result_json = await d3.json (\"https://data.hyphy.org/web/busted-e/busted-phe/\" + dataset);","pinned":false,"hidden":false,"mode":"ojs"},{"id":30,"value":"array = {\n let ar = [];\n let xvar = selected_branches + '_pval_E'\n let yvar = selected_branches + '_pval'\n for (const item of table_data) {\n // Log each item to check its structure\n return item; // Helps see the structure of each entry\n // Check if `item` is defined and does not have `FG_pval_E`\n if (item && !(xvar in item) || !(yvar in item)) {\n ar.push(item);\n }\n }\n console.log(\"Items without xvar or yvar:\", ar); // Logs any items missing these properties\n return ar;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":71,"value":"pvcut = 0.05","pinned":false,"hidden":false,"mode":"ojs"},{"id":462,"value":"ensembl_convert = FileAttachment(\"all_genes.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":435,"value":"$34","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W35","stdlib":"1","titling":"auto"}