31:T570,canvas = { const h = filtered_sims.length; if (h) { const w = 300; const R = 2; const context = DOM.context2d(w*R*2, 2*h*R, 1); for (let i = 0; i < h; i++) { let from = 0.; let to = filtered_sims[i].p1_t; context.fillStyle = omega_color (filtered_sims[i].w1_t); context.fillRect( from*w*R, i*2*R, R*(to-from)*w, R ); from = to; to += filtered_sims[i].p2_t; context.fillStyle = omega_color (filtered_sims[i].w2_t); context.fillRect( from*w*R, i*2*R, R*(to-from)*w, R ); from = to; to += filtered_sims[i].p3_t; context.fillStyle = omega_color (filtered_sims[i].w3_t); context.fillRect( from*w*R, i*2*R, R*(to-from)*w, R ); from = 0.; to = filtered_sims[i].p1_b; context.fillStyle = omega_color (filtered_sims[i].w1_b); context.fillRect( from*w*R, i*2*R + R, R*(to-from)*w, R ); from = to; to += filtered_sims[i].p2_b; context.fillStyle = omega_color (filtered_sims[i].w2_b); context.fillRect( from*w*R, i*2*R + R , R*(to-from)*w, R ); from = to; to += filtered_sims[i].p3_b; context.fillStyle = omega_color (filtered_sims[i].w3_b); context.fillRect( from*w*R, i*2*R + R , R*(to-from)*w, R ); } return context.canvas; } return DOM.context2d(1,1,1).canvas; }32:T4a1,omega_params = { let params = [] params["HackMD_ex0"] = { FG: [0.1,0.5,0.5,0.3,1.0,0.2], BG: [0.1,0.5,0.5,0.3,1.0,0.2] } params["HackMD_ex1"] = { FG: [0.0,0.5,0.1,0.3,0.5,0.2], BG: [0.0,0.5,0.1,0.3,0.5,0.2] } params["HackMD_ex2"] = { FG: [0.0,0.5,0.5,0.3,5,0.2], BG: [0.0,0.5,0.5,0.3,5,0.2] } params["HackMD_ex3"] = { FG: [0.0,0.5,0.5,0.3,1,0.2], BG: [0.0,0.5,0.5,0.3,5,0.2] } params["HackMD_ex4"] = { FG: [0.0,0.5,0.5,0.3,5,0.2], BG: [0.0,0.5,0.5,0.3,1,0.2] } params["HackMD_ex5"] = { FG: [0.1,0.5,0.5,0.3,5,0.2], BG: [0.1,0.5,0.5,0.3,3,0.2] } params["HackMD_ex6"] = { FG: [0.1,0.5,0.5,0.3,3,0.2], BG: [0.1,0.5,0.5,0.3,5,0.2] } return params } // let foreground= {[0.1,0.5,0.5,0.3,1.0,0.2], [0.0,0.5,0.1,0.3,0.5,0.2], [0.0,0.5,0.5,0.3,5,0.2], [0.0,0.5,0.5,0.3,1,0.2], [0.0,0.5,0.5,0.3,5,0.2], [0.1,0.5,0.5,0.3,5,0.2], [0.1,0.5,0.5,0.3,3,0.2]} // let background={[0.1,0.5,0.5,0.3,1.0,0.2], [0.0,0.5,0.1,0.3,0.5,0.2], [0.0,0.5,0.5,0.3,5,0.2], [0.0,0.5,0.5,0.3,5,0.2], [0.0,0.5,0.5,0.3,1,0.2], [0.1,0.5,0.5,0.3,3,0.2] [0.1,0.5,0.5,0.3,5,0.2]}33:T9d3,decision_tree = { if (pv_table[2]["Pos rate (test)"] < .5) { return ("**there is no evidence of selection associated with the chosen phenotype.** \n\nOnly " + String(Math.round(pv_table[2]["Pos rate (test)"]*10000)/100) + "% of simulations show evidence of positive selection in the foreground at p< 0.05") } else { if (pv_table[2]["Pos rate (background)"] < .5) { if (pv_table[2]["Pos rate (different)"] < .5) { return "there is evidence of selection associated with the chosen phenotype, but no statistically significant difference between the test and background selective regimes." } else { return ("**there is strong evidence of selection is associated with the chosen phenotype.** \n\n" + String(Math.round(pv_table[2]["Pos rate (test)"]*10000)/100) + "% of simulations show evidence of positive selection in the foreground, while only " + String(Math.round(pv_table[2]["Pos rate (background)"]*10000)/100) + "% of simulations show evidence for positive selection in the background. " + String(Math.round(pv_table[2]["Pos rate (different)"]*10000)/100) + "% of simulations have statiscically different foreground and background selective regimes at p< 0.05") } } else { if (pv_table[2]["Pos rate (different)"] < .5) { return ("**selection is occurring with or without the chosen phenotype, but with similar selective regimes:** \n\n" + String(Math.round(pv_table[2]["Pos rate (test)"]*10000)/100) + "% of simulations show evidence for positive selection in the foreground, and " + String(Math.round(pv_table[2]["Pos rate (background)"]*10000)/100) + "% of simulations show evidence for positive selection in the background. However, only " + String(Math.round(pv_table[2]["Pos rate (different)"]*10000)/100) + "% of simulations have statistically different foreground and background selective regimes. ") } else { return ("selection is occurring with or without the chosen phenotype, but with different selective regimes. \n\n" + String(Math.round(pv_table[2]["Pos rate (test)"]*10000)/100) + "% of simulations show evidence for positive selection in the foreground, and only " + String(Math.round(pv_table[2]["Pos rate (background)"]*10000)/100) + "% of simulations show evidence for positive selection in the background. " + String(Math.round(pv_table[2]["Pos rate (different)"]*10000)/100) + "% of simulations have statistically different foreground and background selective regimes. ") } } } }34:[{"id":"9fbf4fb601ce6c9ff39cf8cbe274719c3c28cd6f9dcd68530f9fc342919c584fe8f26e016bb1f0c372736451a45602eed43a014a447c85e871f17b24705baa8a","href":"https://static.observableusercontent.com/files/9fbf4fb601ce6c9ff39cf8cbe274719c3c28cd6f9dcd68530f9fc342919c584fe8f26e016bb1f0c372736451a45602eed43a014a447c85e871f17b24705baa8a","name":"sim_data.csv","type":"text/csv","lastModified":1664834497714.207,"size":885161},{"id":"d1444277a6a36b703bb6fdf732a7e67741076fd1a7531ca92526717a9371e910767684318ebde0a17f2252f5bbab6a7377a16490115496ccc9bc19986ca15557","href":"https://static.observableusercontent.com/files/d1444277a6a36b703bb6fdf732a7e67741076fd1a7531ca92526717a9371e910767684318ebde0a17f2252f5bbab6a7377a16490115496ccc9bc19986ca15557","name":"sim_nosrv_data@1.csv","type":"text/csv","lastModified":1667506661247.734,"size":1048251},{"id":"fec0fb8b5b117944bd3c7ec89e2d879496156ec3153463ab94faedaf84749fa342de39bed4a6f07bb6671543c26b39fa88398d0d9e9b2ebbc15f3ffc70a8524a","href":"https://static.observableusercontent.com/files/fec0fb8b5b117944bd3c7ec89e2d879496156ec3153463ab94faedaf84749fa342de39bed4a6f07bb6671543c26b39fa88398d0d9e9b2ebbc15f3ffc70a8524a","name":"sim_data@2.csv","type":"text/csv","lastModified":1667487652750.513,"size":1043549}] 2f:{"title":"BUSTED-PH sims for prelim exam","cells":[{"id":0,"value":"# BUSTED-PH sims for prelim exam","pinned":false,"hidden":false,"mode":"md"},{"id":682,"value":"#### This notebook is for visualizing simulation results used to test BUSTED-PH. To view: it is important to both select a simulation and select the SRV status. ","pinned":false,"hidden":false,"mode":"md"},{"id":18,"value":"viewof which_sim = Inputs.select(uniqueSims, {label: \"Show this sim:\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":581,"value":"viewof srv_yn = Inputs.radio([\"SRV\", \"without SRV\"], {label: \"Account for SRV?\",value: \"SRV\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":138,"value":"#### Simulation parameters used:","pinned":false,"hidden":false,"mode":"md"},{"id":250,"value":"Inputs.table(filtered_omega)","pinned":false,"hidden":false,"mode":"ojs"},{"id":691,"value":"//dotplot = Plot.dot(filtered_sims, {x: \"w3_t\", y: \"p3_t\"}).plot()","pinned":true,"hidden":false,"mode":"ojs"},{"id":284,"value":"#### P-value analysis:","pinned":false,"hidden":false,"mode":"md"},{"id":70,"value":"Inputs.table(pv_table)","pinned":false,"hidden":false,"mode":"ojs"},{"id":353,"value":"_Interpretation:_\n\n**For ${which_sim} simulation ${srv_yn};** ${decision_tree}","pinned":false,"hidden":false,"mode":"md"},{"id":29,"value":"vegalite ({\n \"data\" : {\"values\" : filtered_sims},\n \"columns\" : 3,\n \"hconcat\" : _.map ([[\"p_test\", \"p (test for positive selection in T)\"],[\"p_background\", \"p (test for positive selection in B)\"],[\"p_diff\", \"p (test for difference between T and B)\"]], (d)=> {return {\n \"transform\": [{\n \"sort\": [{\"field\": d[0]}],\n \"window\": [{\"op\": \"count\", \"field\": \"count\", \"as\": \"Cumulative Count\"}],\n \"frame\": [null, 0]\n }],\n \"mark\": {\"type\" : \"area\", \"line\" : true, \"opacity\" : 0.25},\n \"encoding\": {\n \"x\": {\n \"field\": d[0],\n \"type\": \"quantitative\",\n \"title\" : d[1]\n },\n \"y\": {\n \"field\": \"Cumulative Count\",\n \"type\": \"quantitative\",\n \n }\n }\n}})});","pinned":false,"hidden":false,"mode":"ojs"},{"id":84,"value":"Legend(omega_color, {\n title: \"dN/dS\",\n tickFormat: \".2\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":77,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":87,"value":"omega_color = d3.scaleDiverging([10, 1, 0], d3.interpolatePiYG)","pinned":false,"hidden":false,"mode":"ojs"},{"id":411,"value":"validateValue = (t)=> {\n console.log (t.value);\n let tt = parseFloat (t.value);\n if (tt >= 0 && tt <= 1) return true;\n return false;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":398,"value":"p_lrt_fg = {\n var array = filtered_sims.map(d => ({ \"p-value\": d[\"p_test\"], \"LRT\": d[\"lrt_t\"]}))\n return array\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":473,"value":"p_lrt_bg = {\n var array = filtered_sims.map(d => ({ \"p-value\": d[\"p_background\"], \"LRT\": d[\"lrt_b\"]}))\n return array\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":476,"value":"p_lrt_df = {\n var array = filtered_sims.map(d => ({ \"p-value\": d[\"p_diff\"], \"LRT\": d[\"lrt_d\"]}))\n return array\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":55,"value":"filtered_sims = {\n let filtered = sims.filter(d => d.Simulation === which_sim)\n if (srv_yn === \"SRV\") { \n return filtered.filter(d => d.params === \"SRV\")\n } else if (srv_yn === \"without SRV\") {\n return filtered.filter(d => d.params === \"NO SRV\")\n } \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":20,"value":"uniqueSims = _.keys (_.countBy (sims, (d)=>d.Simulation))","pinned":false,"hidden":false,"mode":"ojs"},{"id":53,"value":"pv_table = {\n return _.map (pcut, (pc)=> {\n return {\n 'p' : pc,\n 'Pos rate (test)' : _.filter (filtered_sims, (d)=>d.p_test <= pc).length / filtered_sims.length ,\n 'Pos rate (background)' : _.filter (filtered_sims, (d)=>d.p_background <= pc).length / filtered_sims.length,\n 'Pos rate (different)' : _.filter (filtered_sims, (d)=>d.p_diff <= pc).length / filtered_sims.length \n };\n });\n\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":50,"value":"pcut = [0.001,0.01,0.05]","pinned":false,"hidden":false,"mode":"ojs"},{"id":130,"value":"sims_srv_str = {\nlet arr = FileAttachment(\"sim_data@2.csv\").csv()\n return arr\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":590,"value":"sims_nosrv_str = FileAttachment(\"sim_nosrv_data@1.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":608,"value":"sims = {\n let srv = []\nfor(let i = 0; i < sims_srv_str.length; i ++){\n srv[i] = {}\n for(let j in sims_srv_str[i]){\n if (isNaN(Number(sims_srv_str[i][j]))){\n srv[i][j] = sims_srv_str[i][j]\n }\n else if(typeof Number(sims_srv_str[i][j]) === 'number'){\n srv[i][j] = Number(sims_srv_str[i][j])\n }\n }\n }\n srv = srv.map(d => ({...d, params: \"SRV\" }) )\n let nosrv = [] \n for(let i = 0; i < sims_nosrv_str.length; i ++){\n nosrv[i] = {}\n for(let j in sims_nosrv_str[i]){\n if (isNaN(Number(sims_nosrv_str[i][j]))){\n nosrv[i][j] = sims_nosrv_str[i][j]\n }\n else if(typeof Number(sims_nosrv_str[i][j]) === 'number'){\n nosrv[i][j] = Number(sims_nosrv_str[i][j])\n }\n }\n }\n nosrv = nosrv.map(d => ({...d, params: \"NO SRV\"}) )\n\n let array = srv.concat(nosrv)\n return array\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":316,"value":"sims_srv = {\nlet str = []\nfor(let i = 0; i < sims_srv_str.length; i ++){\n str[i] = {}\n for(let j in sims_srv_str[i]){\n if (isNaN(Number(sims_srv_str[i][j]))){\n str[i][j] = sims_srv_str[i][j]\n }\n else if(typeof Number(sims_srv_str[i][j]) === 'number'){\n str[i][j] = Number(sims_srv_str[i][j])\n }\n }\n }\nreturn str\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":14,"value":"vegalite = require (\"vega-embed\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":80,"value":"import {Legend, Swatches} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":450,"value":"import {rejected} \nwith {pv_data as p_adjusted}\nfrom \"@spond/evaluate-different-forms-of-multiple-testing-correction\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":173,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":236,"value":"filtered_omega = {\n let FG = omega_params[which_sim][\"FG\"]\n let BG = omega_params[which_sim][\"BG\"]\n let table = []\n let headers = [\"omega_1\", \"rate_1\", \"omega_2\", \"rate_2\", \"omega_3\", \"rate_3\"]\n table[0] = {Partition: \"FG\"}\n table[1] = {Partition: \"BG\"}\n for (let index = 0; index < headers.length; ++index) {\n table[0][headers[index]] = FG[index]\n table[1][headers[index]] = BG[index]\n }\n return table \n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":348,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":392,"value":"import {select, checkbox, autoSelect} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":430,"value":"colors = d3.scaleOrdinal([\"p-value\", \"No correction\", \"FDR\", \"Bonferroni\", \"Holm-Bonferroni\"], d3.schemeCategory10)","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W34","stdlib":"1","titling":"auto"}