30:T5bb,plot_power_curve = (data, field, step, p, pfield) => { pfield = pfield || "p21"; _.each (data, (d)=>{ d.called = d[pfield] <= p; }); return vegalite ({"data": {values : data}, "width" : 500, "height" : 500, "layer" : [ { "mark": { "type" : "line", "strokeWidth" : 5, "interpolate" : "monotone" }, "encoding": { "x": { "field": field[0], "type": "quantitative", "bin" : { "binned" : true, "step" : step }, }, "y": { "aggregate" : "q3", "field": pfield, "type": "quantitative", "scale" : { "type" : "linear", } }, } }, { "mark": { "type" : "circle", "color" : "#f58518" }, "encoding": { "x": { "field": field[0], "type": "quantitative", "bin" : { "binned" : true, "step" : step }, }, "y": { "aggregate" : "q3", "field": pfield, "type": "quantitative", }, "size": { "aggregate": "count", "type": "quantitative", "legend" : {"title" : "Samples", "titleFontSize": 20, "orient" : "right", "labelFontSize" : 14}, } } } ], "config": { "view": { "stroke": "transparent" } }}) }31:T402,compute_metrics = (data, accessor, p_crit, label) => { var false_positives = 0, false_negatives = 0, true_positives = 0, true_negatives = 0; _.each (data, (d) => { var p = accessor (d); var l = label (d); if (l) { if (p <= p_crit) { true_positives++; } else { false_negatives++; } } else { if (p <= p_crit) { false_positives++; } else { true_negatives++; } } }); var N = true_positives + false_positives + true_negatives + false_negatives; return { 'p' : p_crit, 'N' : N, 'tp' : true_positives, 'fp' : false_positives, 'tn' : true_negatives, 'fn' : false_negatives, 'fpr' : false_positives / (true_negatives + false_positives), 'power' : true_positives / (true_positives + false_negatives), 'ppv' : true_positives / (true_positives + false_positives) }; };32:T43f,compute_roc = (data, accessor, step, label) => { var aoc_by_step = [[0,0,0,0]]; var sorted_list = []; var total_positives = 0, total_negatives = 0; _.each (data, (d) => { var p = accessor (d); var l = label (d); if (l) { total_positives ++; } else { total_negatives ++; } sorted_list.push ([p,l]); }); sorted_list.sort ((a,b) => a[0]-b[0]); var index = 0; var true_calls = 0, false_calls = 0; for (var p = step; p <= 1 + (step/2); p+=step) { while (index < sorted_list.length && sorted_list[index][0] <= p) { if (sorted_list[index][1]) { true_calls++; } else { false_calls ++; } index ++; } aoc_by_step.push ([p, true_calls+false_calls,true_calls/total_positives,false_calls/total_negatives, true_calls/(true_calls+false_calls)]); } return _.map (aoc_by_step, (d) => {return {'fp' : d[3], 'power' : d[2], 'ppv' : d[4], "p" : d[0]}}); };33:T82b,plot_prc = (plot_data, labels) => { var merged_data = []; _.each (plot_data, (d,i) => { _.each (d, (e) => { e.label = labels[i]; merged_data.push (e); }); }); var crticial_values = _.filter (merged_data, (d)=>Math.abs (d.p - 0.01) < 1e-5 || Math.abs (d.p - 0.05) < 1e-5 || Math.abs (d.p - 0.1) < 1e-5); return vegalite ({ "layer" : [{ "data": {values : merged_data}, "mark": { "type": "line", "interpolate": "monotone", "strokeWidth" : 5 }, "width" : 500, "height" : 500, "encoding": { "x": { "field": "power", "axis":{ "title" : "Recall", grid : false, titleFontSize: 18, labelFontSize: 14, format : "g" }, "type": "quantitative" }, "y": { "field": "ppv", "type": "quantitative", "axis":{ "title" : "Precision", grid : false, titleFontSize: 18, labelFontSize: 14, format : "g" } }, "color" : { "field" : "label", "type" : "nominal", "legend" : {"title" : "Simulation", "titleFontSize": 1, "orient" : "right", "labelFontSize" : 14}, } } }, { "data": {values : crticial_values}, "mark": { "type": "point", "size" : 400, "filled" : true }, "encoding": { "x": { "field": "power", "axis":{ "title" : "Recall", grid : false, titleFontSize: 14, labelFontSize: 12, format : "g" }, "type": "quantitative" }, "y": { "field": "ppv", "type": "quantitative", "axis":{ "title" : "Precision", grid : false, titleFontSize: 16, labelFontSize: 12, format : "g" } }, "color" : { "field" : "label", "type" : "nominal" } } }] , "config": { "view": { "stroke": "transparent" } }}); }34:T4b7,plot_qq = (plot_data, label) => { return vegalite ({"data": {values : plot_data}, "layer" : [{ "mark": { "type": "line", "interpolate": "monotone" }, "width" : 300, "height" : 300, "encoding": { "x": { "field": "expected", "axis":{ "title" : "Theoretical", grid : false, titleFontSize: 14, labelFontSize: 12, format : "g" }, "type": "quantitative" }, "y": { "field": "observed", "type": "quantitative", "axis":{ "title" : "Observed", grid : false, titleFontSize: 16, labelFontSize: 12, format : "g" } } } }, { "mark": { "type": "line", "interpolate": "monotone", "color" : "grey", "strokeDash" : [3,3] }, "width" : 800, "height" : 800, "encoding": { "x": { "field": "expected", "type": "quantitative" }, "y": { "field": "expected", "type": "quantitative", } } } ], "config": { "view": { "stroke": "transparent" } }}); }35:[] 2e:{"title":"Multi-hit simulations","cells":[{"id":0,"value":"md`# Multi-hit simulations\n\nExploration of null simulation results for the multiple hit model\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":503,"value":"/*plot_prc ([compute_roc (_.filter (sim_data, (d) => d.variable && (d.rate_diff < 1)), (d)=>d.p, 0.01, (d)=>d.beta1 != d.beta2), compute_roc (_.filter (sim_data, (d) => d.variable && (d.rate_diff >= 1) || (d.rate_diff == 0)), (d)=>d.p, 0.01, (d)=>d.beta1 != d.beta2)],[\"Small effect\",\"Large effect\"])*/","pinned":false,"hidden":false,"mode":"ojs"},{"id":384,"value":"plot_qq (_.filter (_.map (compute_roc (_.filter (sim_data, (d)=>true), (d)=>d.p21, 0.005, (d)=>false), (d)=>{return {\"expected\" : d.p, \"observed\" : d.fp}}), (d)=>d.expected <= 0.1))","pinned":false,"hidden":false,"mode":"ojs"},{"id":698,"value":"plot_power_curve (_.filter (sim_data, (d)=>d.L < 4), [\"MaxL\", \"Longest Branch\"], 0.2, 0.01,\"LRT21\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":693,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":239,"value":"/*plot_power_curve (_.filter (power_sims_detectable, (d)=> d.rate_diff_est < 10), [\"rate_diff_est\", \"Effect size\"], 1.)*/","pinned":false,"hidden":false,"mode":"ojs"},{"id":687,"value":"/*vegalite ({\n \n \"layer\" : [{\n \"data\": {values : sim_data},\n \"mark\": {\n \"type\": \"point\",\n },\n \"width\" : 500,\n \"height\" : 500,\n \"encoding\": {\n \"x\": {\n \"field\": \"L\",\n \"axis\":{\n \"title\" : \"Tree Length\",\n grid : false,\n titleFontSize: 18, labelFontSize: 14, format : \"g\"\n },\n \"type\": \"quantitative\"\n },\n \"y\": {\n \"field\": \"MaxL\",\n \"type\": \"quantitative\",\n \"axis\":{\n \"title\" : \"Maximum Branch Length\",\n grid : false,\n titleFontSize: 18, labelFontSize: 14, format : \"g\"\n }\n },\n \"color\" : {\n \"field\" : \"p21\",\n \"type\" : \"quantitative\",\n \"legend\" : {\"title\" : \"Simulation\", \"titleFontSize\": 1, \"orient\" : \"right\", \"labelFontSize\" : 14},\n }\n }\n }]})*/","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"md`------`","pinned":false,"hidden":false,"mode":"ojs"},{"id":287,"value":"sim_data = await d3.csv (\"https://dl.dropbox.com/s/2gt1rvzh6rmrfie/2.seq.results.csv\", d3.autoType)\n //https://dl.dropbox.com/s/8gmtv2jgh8dlhdq/results.csv\n //\"https://dl.dropbox.com/s/2gt1rvzh6rmrfie/2.seq.results.csv\"\",d3.autoType)","pinned":false,"hidden":false,"mode":"ojs"},{"id":520,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":300,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":330,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":381,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"_=require ('lodash')","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"d3 = require(\"d3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":10,"value":"vegalite = require(\"vega-embed@3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":514,"value":"import { table } from \"@gampleman/table\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":816,"value":"_.filter (sim_data, (d)=>d.p21 < 0.01)","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W35","stdlib":"1","titling":"auto"}