2a:Taf6,vegalite ({ "config": { "legend": { "disable" : "false" } }, "repeat": { "row": ["AV_dsn"/*, "TP_dsn", "YHFN_dsn"*/], }, "spec": { width: 800, height: 200, "data": {"values": _.map (_.filter (data, (d)=>d['2HF'] + d['3HF'] > 0 && d['ma_pv'] <= 0.05), (d)=>({'2HF' : Math.min (d['2HF'], 0.05), '3HF' : Math.min (d['3HF'], 0.05)}))}, "layer" : [ { /*"transform":[{ "density": "2HF", //"groupby": ["kind"], "bandwidth": 0.001 }],*/ //"mark": {type: "bar", "opacity" : 0.7}, "mark": {type: "bar", "opacity" : 0.5, tooltip : true, line : true, clip : true}, "encoding": { "x": {"field": "2HF", "type": "quantitative", "bin": {"maxbins": 50}, //"scale" : {"domain" : [0,0.1], "zero" : false}, "title" : "MH contribution", "axis" : {"grid" : false, titleFontSize : 18, labelFontSize: 14, "format" : "2p"} }, "y": {"aggregate": "count", "axis" : {"grid" : false, "title" : "Alignments", titleFontSize : 18, labelFontSize: 14}, "type": "quantitative", "scale" : {"type" : "log"}}, "color" : {"value": "grey"}, } }, { /*"transform":[{ "density": "2HF", //"groupby": ["kind"], "bandwidth": 0.001 }],*/ //"mark": {type: "bar", "opacity" : 0.7}, "mark": {type: "bar", "opacity" : 0.5, tooltip : true, line : true, clip : true}, "encoding": { "x": {"field": "3HF", "type": "quantitative", "bin": {"maxbins": 50}, //"scale" : {"domain" : [0,0.1], "zero" : false}, "axis" : {"grid" : false, titleFontSize : 18, labelFontSize: 14} }, "y": {"aggregate": "count", "axis" : {"grid" : false, titleFontSize : 18, labelFontSize: 14}, "type": "quantitative"}, "color" : {"value": "firebrick"} } }, /*{ "mark": "rule", "encoding": { "x": {"aggregate": "median", "field": "2HF"}, "color": {"value": "gray"}, "size": {"value": 5}, } }, { "transform": [ { "aggregate": [{"op": "mean", "field": "2HF", "as": "dsn_mean1"}] }, {"calculate": "'AV='+format(datum['dsn_mean1'], '.2p')", "as": "fm1"} ], "mark": { "type": "text", "color": "gray", "size" : 16, "align": "right", "y": -5 }, "encoding": { "x" : {"field" : "dsn_mean1", "type": "quantitative"}, "text": {"type": "nominal", "field": "fm1"} } },*/ ], }, //config: {"fieldTitle" : "plain"} })2b:T4c8,vegalite({ "config" : { "diverging": {"scheme": "spectral"}, }, "data": {"values":_.filter (addl_null_sims, (d)=>d.psi <= 1)}, "repeat": [ "p_plain", "p_s", "p_MH", "p", "p_ma" ], "columns": 3, "spec" : { "width" : 200, "height" : 200, "mark": "rect", "encoding": { "x": { "bin": {"maxbins": 5}, "field": "delta", "scale" : {"type" : "linear"}, "axis" : {"title" : "δ", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 10} }, "y": { "bin": {"maxbins": 5}, "field": "psi", "scale" : {"type" : "linear"}, "axis" : {"title" : "ψ", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 2} }, "stroke" : {"value" : "black"}, "color": {"field" : {"repeat": "repeat"}, "aggregate": "mean", "scale": { "domainMid": 0.05, "range": "diverging", "reverse" : true, "type" : "sqrt", }, "legend" : { "orient" : "top", "title" : "FP rate", "titleFontSize" : 14, "labelFontSize" : 10, "tickCount" : 5, }} } } }) 2c:T551,vegalite({ "data": {"values":_.flatten(_.map (addl_null_sims, (d)=>{ return _.map ([["p","+S+MH"],["p_s","+S"],["p_MH","+MH"],["p_plain","BUSTED"],["p_ma", "Model-averaged"]], (t)=> { return {"delta": Math.min (0.5,d.delta), "psi": Math.min (1.,d.psi), "p" : d[t[0]], "type" : t[1]}; }); }))}, "width" : 400, "height" : 400, "layer" : [ { "mark": {"type" : "line", "interpolate" : "linear", "point" : true, "size" : 3}, "encoding": { "x": { "bin": {"maxbins": 5}, "field": "psi", "scale" : {"type" : "linear"}, "axis" : {"title" : "ψ", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 10} }, "y": {"field" : "p", "aggregate": "mean", "axis" : {"grid" : false, "title" : "FP rate", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 5}, "scale" : {type : "sqrt"} }, "color": {"field" : "type", "legend" : {"orient" : "top-left", "title" : "Approach", "titleFontSize" : 18, "labelFontSize" : 14}} } }, {"mark": { "type": "rule", "size" : 5, "color": "gray", "opacity" : 0.01 }, "encoding": { "y": { "datum": {"expr": "0.05"}, "type": "quantitative", }, }} ] })2d:T4cf,vegalite({ "config" : { "diverging": {"scheme": "spectral"}, }, "data": {"values":_.filter (addl_power_sims, (d)=>d.omega <= 20)}, "repeat": [ "p_plain", "p_s", "p_MH", "p", "p_ma" ], "columns": 3, "spec" : { "width" : 200, "height" : 200, "mark": "rect", "encoding": { "x": { "bin": {"maxbins": 10}, "field": "delta", "scale" : {"type" : "linear"}, "axis" : {"title" : "δ", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 10} }, "y": { "bin": {"maxbins": 10}, "field": "omega", "scale" : {"type" : "linear"}, "axis" : {"title" : "ω>1", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 2} }, "stroke" : {"value" : "black"}, "color": {"field" : {"repeat": "repeat"}, "aggregate": "mean", "scale": { "domainMid": 0.05, "range": "diverging", "reverse" : true, "type" : "sqrt", }, "legend" : { "orient" : "top", "title" : "Power", "titleFontSize" : 14, "labelFontSize" : 10, "tickCount" : 5, }} } } })2e:T43c,vegalite({ "data": {"values":_.map (addl_power_sims, (d)=>{d.om = Math.min (d.omega, 25); return d;})}, "repeat": [ "p_plain", "p_s", "p_MH", "p", "p_ma" ], "columns": 3, "spec" : { "width" : 200, "height" : 200, "layer" : [ { "mark": "bar", "encoding": { "x": { "bin": {"maxbins": 20}, "field": "om", "scale" : {"type" : "linear"}, "axis" : {"title" : "ω>1", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 10} }, "y": {"field" : {"repeat": "repeat"}, "aggregate": "mean", "axis" : {"grid" : false, "title" : "Detection rate", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 5}, "scale" : {domain : [0,1]} }, "color": {"value" : "#AAA"} } }, {"mark": { "type": "rule", "color": "firebrick" }, "encoding": { "y": { "datum": {"expr": "0.05"}, "type": "quantitative", }, }} ] } })2f:T5ad,vegalite({ "data": {"values":_.flatten(_.map (_.filter (addl_power_sims, (d)=>d.omega >= 4), (d)=>{ return _.map ([["p","+S+MH"],["p_s","+S"],["p_MH","+MH"],["p_plain","BUSTED"],["p_ma", "Model-averaged"]], (t)=> { return {"delta": Math.min (0.2,d.delta), "omega" : Math.min (d.omega, 25), "p" : d[t[0]], "type" : t[1]}; }); }))}, "width" : 400, "height" : 400, "title" : {"text" : "ω≥4", fontSize : 24}, "layer" : [ { "mark": {"type" : "line", "interpolate" : "linear", "point" : true, "size" : 3}, "encoding": { "x": { "bin": {"maxbins": 5}, "field": "delta", "scale" : {"type" : "linear"}, "axis" : {"title" : "δ", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 10} }, "y": {"field" : "p", "aggregate": "mean", "axis" : {"grid" : false, "title" : "Power", "titleFontSize" : 20, "labelFontSize" : 12, "tickCount" : 5}, "scale" : {type : "sqrt"} }, "color": {"field" : "type", "legend" : {"orient" : "top-right", "title" : "Approach", "titleFontSize" : 18, "labelFontSize" : 14}} } }, /*{"mark": { "type": "rule", "size" : 5, "color": "gray", "opacity" : 0.01 }, "encoding": { "y": { "datum": {"expr": "0.05"}, "type": "quantitative", }, }}*/ ] })30:T79d,data_annotator = (data)=> { let rankings = { 'BUSTED' : [], '+S' : [], '+MH' : [], '+S+MH' : [], 'Best' : [], 'Averaged' : [] }; const p = 0.05; const model2key = {'BUSTED' : 'p_plain', '+S' : 'p_s', '+MH' : 'p_MH', '+S+MH' : 'p'}; _.each (data, (d)=> { let local_rank = [['+S+MH', d["AIC-c"]],['BUSTED', d["AIC-c"] + d["plain"]], ['+S', d["AIC-c"] + d["+S"]], ['+MH', d["AIC-c"] + d["+MH"]]]; let slr = _.sortBy (local_rank, (d)=>d[1]); let bestAIC = slr[0][1]; _.each (slr, (d)=> { d[2] = Math.exp (0.5*(bestAIC - d[1])); }); const norm = d3.sum (slr, (d)=>d[2]); d.best_model = slr[0][0]; d.aic_range = slr[3][1]-slr[0][1]; d.aic_top2 = slr[1][1]-slr[0][1]; d.second_best = slr[1][0]; d.pv_best = d[model2key[d.best_model]]; let total = 0; let ma_pv = 0; _.each (model2key, (pv, mdl)=> { if (d[pv] <= p) { rankings[mdl].push (d); total ++;} }); _.each (slr, (m)=> { m[2] /= norm; ma_pv += d[model2key[m[0]]] * m[2]; }); d.aic_weights = slr; d.ma_pv = ma_pv; if (d[model2key[slr[0][0]]] <= p) {rankings['Best'].push (d); total++;} if (ma_pv <= p) {rankings['Averaged'].push (d); total++;} }); let genes = {}; _.each (rankings, (msas, label)=> { _.each (msas, (dataset)=> { const key = dataset.File; if (! (key in genes)) { genes[key] = []; } genes[key].push (label); }); }); _.each (data, (msa)=>{ if (!(msa.File in genes)) { genes[msa.File] = ['None']; } }); _.each (data, (d)=> { if (d.File in genes) { d.classification = new Set (genes[d.File]); } }); return _.map (genes, (labels, key)=>({'name' : key, 'sets': labels})); }31:T63b,vegalite ({ "columns" : 3, "hconcat": _.map ([["D_BUSTED_noS","dist (BUSTED, +MH)", 0.5] , ["D_BUSTED_S","dist (BUSTED, +S)", 0.5], ["D_BUSTED_MH","dist (BUSTED, +S+MH)", 0.5], ["D_S_noS","dist (+S, +MH)", 0.5], ["D_S_MH","dist (+S, +S+MH)", 0.5], ["D_noS_MH","dist (+MH, +S+MH)", 0.5]], (c)=> { return { "data": {"values" : _.map ( _.filter (data, filter_EDS_pattern ([1,1,1,0,1,1], '')), (d)=>({'EDS class' : '(111011)', 'Effect size': c[3] ? Math.min (c[3](d),c[2]) : Math.min (d[c[0]],c[2])})) .concat ( _.map ( _.filter (data, filter_EDS_pattern ([1,1,1,1,1,1], "")), (d)=>({'EDS class' : '(111111)', 'Effect size': c[3] ? Math.min (c[3](d),c[2]) : Math.min (d[c[0]],c[2])})))}, "mark": { "type": "boxplot", "extent": 2.5, "median": {"color": "red"}, "ticks": true, "color" : "#AAA", }, "height" : 80, "width" : 200, "title" : {"text" : c[1], "fontSize" : 20}, "encoding": { "y": {"field": "EDS class", "type": "nominal", "axis" : {"title" : null, "labelFontSize" : 14}}, "x": { "field": "Effect size", "axis" : {"title" : null, "labelFontSize" : 14, "grid" : false}, "type": "quantitative", "scale": {"zero": false, "type" : "symlog"} } } } }) })32:T6d8,support_table_data = _.chain (unique_intersections).filter (d=>d.name != "None").map (d=>{ let record = {'Type' : _.map ([...d.sets], (e)=>e.name).join (", "), "N" : d.elems.length, "BUSTED Sites" : null, "+S Sites" : null, "+MH Sites" : null, "+S+MH Sites" : null, "BUSTED BS" : null, "+S BS" : null, "+MH BS" : null, "+S+MH BS" : null, "BUSTED singles" : null, "+S singles" : null, "+MH singles" : null, "+S+MH singles" : null, "BUSTED p3" : null, "+S p3" : null, "+MH p3" : null, "+S+MH p3" : null, }; const lookup = {"BUSTED" : "_BUSTED", "+S" : "_S", "+S+MH" : "_MH", "+MH" : "_noS"}; const r = by_name [d]; _.each (["BUSTED","+S","+MH","+S+MH"], (t)=> { record [t + " Sites"] = d3.median (_.map (_.filter (d.elems, e=>by_name [e.name]["LRF" + lookup[t]] != "N/A"), e=>by_name [e.name]["LRF" + lookup[t]])); record [t + " BS"] = d3.median (_.map (_.filter (d.elems, e=>by_name [e.name]["EB" + lookup[t]] != "N/A"), e=>by_name [e.name]["EB" + lookup[t]])); record [t + " singles"] = _.filter (d.elems, e=>by_name [e.name]["LRF" + lookup[t]] == 1).length / _.filter (d.elems, e=>by_name [e.name]["LRF" + lookup[t]] != "N/A").length; record [t + " p3"] = d3.mean (d.elems, e=>by_name [e.name]["p3" + lookup[t]]); }); return record; }).value()33:T5f4,contrast_plot = (agg,filter,plot_title, axis_label) => ({ "data": {"values": binByGene (data, 0.05, agg, filter)}, "title" : plot_title, "resolve": {"scale": {"x": "independent"}}, "hconcat" : [{ "mark": { "type": "boxplot", "extent": "min-max" }, //height : 200, "encoding": { "y": {"field": "ps", "type": "nominal", "scale" : {"domain" : ['--','++','-+','+-']}, "axis" : {"title" : "Classification", "titleFontSize": 16, "labelFontSize" : 16, "labelFont" : "courier"}}, "x": { "field": "delta", "type": "quantitative", "scale": {"zero": false, "type" : "sqrt"}, "axis" : {"title" : axis_label, "titleFontSize": 14}, }, "color" : {"value" : "purple"} } }, { "mark": { "type": "rect", //"extent": "min-max" }, //height : 200, "encoding": { "y": {"field": "ps", "type": "nominal", "scale" : {"domain" : ['--','++','-+','+-']}, "axis" : {"title" : "", "labels" : false, "titleFontSize": 16, "labelFontSize" : 16, "labelFont" : "courier"}}, "x": { "field": "delta", "type": "quantitative", "bin": {"maxbins":60}, "scale": {"type" : "linear"}, "axis" : {"title" : axis_label, "titleFontSize": 14}, }, "color": { "aggregate": "count", "type": "quantitative", "title" : "Count", "legend" : {"orient" : "bottom"}, "scale" : {"type" : "symlog","scheme": "purples"} } } }] })34:T6e9,compareEstimates = (data, field, title_x, title_y, field_2) => ( { "data": {"values": data}, "hconcat" : [{ "width" : 400, "height" : 400, "mark": "rect", "transform": [ {"filter" : "datum['+S'] > 0"} ], "title" : {"text" :"Multi-hit preferred by cAIC", "fontSize" : 20}, "encoding": { "x": {"field": field, "type": "quantitative", "scale" : {"type" : "linear"}, "axis" : {"title" : title_x, "titleFontSize" : 18, "tickCount" : 10}, "bin": {"maxbins":50}}, "y": {"field": field_2, "type": "quantitative", "scale" : {"type" : "linear"},"axis" : {"tickCount" : 10, "title" : title_y, "titleFontSize" : 18}, "bin": {"maxbins":50}}, "size" : {"value" : 5}, "color": { "aggregate": "count", "type": "quantitative", "title" : "Count", "legend" : {"orient" : "bottom"}, "scale" : {"type" : "symlog","scheme": "purples"} } } }, { "title" : {"text" :"Single-hit preferred by cAIC", "fontSize" : 20}, "width" : 400, "height" : 400, "mark": "rect", "transform": [ {"filter" : "datum['+S'] < 0"} ], "encoding": { "x": {"field": field, "type": "quantitative", "scale" : {"type" : "linear"}, "axis" : {"title" : title_x, "titleFontSize" : 18, "tickCount" : 10}, "bin": {"maxbins":50}}, "y": {"field": field_2, "type": "quantitative", "scale" : {"type" : "linear"},"axis" : {"tickCount" : 10, "title" : "", "titleFontSize" : 18}, "bin": {"maxbins":50}}, "size" : {"value" : 5}, "color": { "aggregate": "count", "type": "quantitative", "title" : "Count", "legend" : {"orient" : "bottom"}, "scale" : {"type" : "symlog","scheme": "purples"} } } }] } )35:[] 29:{"title":"BUSTED[S] vs BUSTED[S]-MH","cells":[{"id":4,"value":"# BUSTED[S] vs BUSTED[S]-MH\n","pinned":false,"hidden":false,"mode":"md"},{"id":507,"value":"viewof dataset = Inputs.select(data_sources, {label: \"Dataset\", format: x => x.label, value: data_sources.find(t => t.label === \"Selectome\")})","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"viewof search = Inputs.search(data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"Inputs.table(search, {\n format: {\n Year: d3.format(\"d\") // format as \"1960\" rather than \"1,960\"\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1018,"value":"viewof selection = UpSetJSElement(detection_sets, detection_intersections, {'width' : 1400, 'heightRatios' : [0.7],'widthRatios' : [115,75], 'theme' : 'light', 'exportButtons' : false, 'fontSizes' : {'barLabel' : \"8px\", \"setLabel\" : \"12px\"}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":219,"value":"md`**Table 1**. Method performance comparison (all data, p = 0.05)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":153,"value":"twoByTwo (...getCounts (pv))","pinned":false,"hidden":false,"mode":"ojs"},{"id":223,"value":"md`**Table 2**. Method performance comparison (all data, p = 0.001)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":226,"value":"twoByTwo (...getCounts (pv, 0.001))","pinned":false,"hidden":false,"mode":"ojs"},{"id":229,"value":"md`**Table 3**. Method performance comparison (MH preferred, p = 0.05)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":233,"value":"twoByTwo (...getCounts (_.filter (pv, (datum)=>datum['BUSTEDS|cAIC'] > datum['BUSTEDS-MH|cAIC'])))","pinned":false,"hidden":false,"mode":"ojs"},{"id":239,"value":"md`**Table 4**. Method performance comparison (SH preferred, p = 0.05)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":242,"value":"twoByTwo (...getCounts (_.filter (pv, (datum)=>datum['BUSTEDS|cAIC'] < datum['BUSTEDS-MH|cAIC'])))","pinned":false,"hidden":false,"mode":"ojs"},{"id":296,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.min (10,d.delta);}, \n (d)=>d[\"+S\"] > 0,\"+S+MH preferred by AIC-c\", \"δ (2H) rate\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":399,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.min (10,d.delta);}, \n (d)=>d[\"+S\"] < 0,\"+S preferred by AIC-c\", \"δ (2H) rate\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":374,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.min (10,d.psi);}, \n (d)=>d[\"+S\"] > 0,\"MH preferred by AIC\", \"Triple hit rate\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":576,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.min (10,d.psi);}, \n (d)=>d[\"+S\"] < 0,\"SH preferred by AIC\", \"Triple hit rate\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":461,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.max (-2, Math.min (2,d.omega1_MH * d.p1_MH + d.omega2_MH * d.p2_MH + d.omega3_MH * d.p3_MH - d.omega1_S * d.p1_S - d.omega2_S * d.p2_S - d.omega3_S * d.p3_S ));}, \n (d)=>d[\"+S\"] >= 0,\"MH preferred by AIC\",\"E [MH-ω - SH-ω]\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":519,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.max (-2, Math.min (2,d.omega1_MH * d.p1_MH + d.omega2_MH * d.p2_MH + d.omega3_MH * d.p3_MH - d.omega1_S * d.p1_S - d.omega2_S * d.p2_S - d.omega3_S * d.p3_S ));}, \n (d)=>d[\"+S\"] < 0,\"SH preferred by AIC\",\"E [MH-ω - SH-ω]\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":563,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.sqrt(d.N * d.S);}, \n (d)=>d[\"+S\"] > 0, \"MH preferred by AIC\",\"Sqrt (Sample Size)\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":480,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.max (-2, Math.min (2,d.omega1_MH * d.p1_MH - d.omega1_S * d.p1_S));}, \n (d)=>d[\"+S\"] > 0,\"MH preferred by AIC\",\"MH-ω1 - SH-ω1\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":487,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.max (-2, Math.min (2,d.omega2_MH * d.p2_MH - d.omega2_S * d.p2_S));}, \n (d)=>d[\"+S\"] > 0,\"MH preferred by AIC\",\"MH-ω2 - SH-ω2\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":491,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.max (-4, Math.min (4,d.omega3_MH * d.p3_MH - d.omega3_S * d.p3_S));}, \n (d)=>d[\"+S\"] > 0,\"MH preferred by AIC\",\"MH-ω3 - SH-ω3\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":516,"value":"vegalite (contrast_plot (\n (d, res)=> {res.delta = Math.max (-4, Math.min (4,d.omega3_MH * d.p3_MH - d.omega3_S * d.p3_S));}, \n (d)=>d[\"+S\"] < 0,\"SH preferred by AIC\",\"MH-ω3 - SH-ω3\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":71,"value":"vegalite (compareEstimates (data, \"p_s\", \"SH p\", \"MH p\", \"p\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":430,"value":"vegalite (compareEstimates (data, \"SRV_S\", \"SH CV(alpha)\", \"MH CV(alpha)\", \"SRV_MH\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":776,"value":"vegalite (compareEstimates (_.filter (data, (d)=>d[\"p_s\"] < 0.05 && d[\"p\"] >= 0.05), \"p_s\", \"SH selected\", \"MH selected\", \"p\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":530,"value":"vegalite (compareEstimates (_.map (_.filter (data, (d)=>d[\"p_s\"] < 0.05 && d[\"p\"] >= 0.05), (d)=> {d.delta_p = Math.log10 (Math.max (1e-20,d.p)) - Math.log10 (Math.max (1e-20,d.p_s)); return d;}), \"delta_p\", \"log (p|MH) - log (p|SH)\", \"DH Rate\",\"delta\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1804,"value":"$2a","pinned":false,"hidden":false,"mode":"ojs"},{"id":2102,"value":"$2b","pinned":false,"hidden":false,"mode":"ojs"},{"id":2243,"value":"$2c","pinned":false,"hidden":false,"mode":"ojs"},{"id":2215,"value":"$2d","pinned":false,"hidden":false,"mode":"ojs"},{"id":2268,"value":"$2e","pinned":false,"hidden":false,"mode":"ojs"},{"id":2364,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":68,"value":"pv = contrastByGene (data, [\"p\", \"p_s\", \"AIC-c\", \"+S\", \"delta\"], (d)=> {\n d[\"BUSTEDS-MH|LRT p-value\"] = d.p;\n d[\"BUSTEDS|LRT p-value\"] = d.p_s;\n d[\"BUSTEDS-MH|cAIC\"] = d[\"AIC-c\"];\n d[\"BUSTEDS|cAIC\"] = d[\"AIC-c\"] + d[\"+S\"];\n d[\"BUSTEDS-MH|DH_Rate\"] = Math.min (1, d[\"delta\"]);\n /*d[\"BUSTEDS|delta\"] = Math.log (Math.max (1e-10,d[\"BUSTEDS-MH|LRT p-value\"])) - Math.log (Math.max (1e-10,d[\"BUSTEDS|LRT p-value\"]));\n d[\"BUSTEDS-MH|selected\"] = Math.log (Math.max (1e-10,d[\"BUSTEDS-MH|p3\"]*d[\"BUSTEDS-MH|w3\"]));\n d[\"BUSTEDS|selected\"] = Math.log (Math.max (1e-10,d[\"BUSTEDS|p3\"]*d[\"BUSTEDS|w3\"]));*/\n return d;\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":585,"value":"for_par_cor = contrastByGene (data, [\"LRT p-value\",\"cAIC\",\"DH_Rate\",\"TH_Rate\",\"w3\"], (d)=> {\n d[\"class\"] = (d[\"BUSTEDS|LRT p-value\"] <= 0.05 ? \"+\" : \"-\") + (d[\"BUSTEDS-MH|LRT p-value\"] <= 0.05 ? \"+\" : \"-\");\n d[\"DH_Rate\"] = Math.min (0.5, d[\"BUSTEDS-MH|DH_Rate\"]);\n d[\"TH_Rate\"] = Math.min (0.5, d[\"BUSTEDS-MH|TH_Rate\"]);\n d[\"MH|omega3\"] = Math.log (d[\"BUSTEDS-MH|w3\"]);\n d[\"SH|omega3\"] = Math.log (d[\"BUSTEDS|w3\"]);\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":425,"value":"srv = contrastByGene (data, [\"cAIC\", \"CV(alpha)\"])","pinned":false,"hidden":false,"mode":"ojs"},{"id":436,"value":"omega = contrastByGene (data, [\"cAIC\", \"w1\",\"w2\",\"w3\",\"p1\",\"p2\",\"p3\"], (d)=> {\n d[\"BUSTEDS|mean\"] = Math.min (2, d[\"BUSTEDS|w1\"] * d[\"BUSTEDS|p1\"] + d[\"BUSTEDS|w2\"] * d[\"BUSTEDS|p2\"] + d[\"BUSTEDS|w3\"] * d[\"BUSTEDS|p3\"]) ;\n d[\"BUSTEDS-MH|mean\"] = Math.min( d[\"BUSTEDS-MH|w1\"] * d[\"BUSTEDS-MH|p1\"] + d[\"BUSTEDS-MH|w2\"] * d[\"BUSTEDS-MH|p2\"] + d[\"BUSTEDS-MH|w3\"] * d[\"BUSTEDS|p3\"],2 );\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":504,"value":"data_sources = [\n {'url' : 'https://data.hyphy.org/web/busted-mh/enard-2023.csv', 'label' : \"ENARD\"},\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1725,"value":"d3.quantile (_.map (_.filter (data, (d)=>d.best_model == \"+S+MH\"), (d)=>d.delta), 0.975)","pinned":false,"hidden":false,"mode":"ojs"},{"id":950,"value":"compute_aic_ranking = {\n let rankings = {\n 'BUSTED' : [[],[],[],[]],\n '+S' : [[],[],[],[]],\n '+MH' : [[],[],[],[]],\n '+S+MH' : [[],[],[],[]]\n };\n\n _.each (_.filter (data, (d)=>d.classification), (d)=> {\n let local_rank = [['+S+MH', d[\"AIC-c\"]],['BUSTED', d[\"AIC-c\"] + d[\"plain\"]], ['+S', d[\"AIC-c\"] + d[\"+S\"]], ['+MH', d[\"AIC-c\"] + d[\"+MH\"]]];\n _.each (_.sortBy (local_rank, (d)=>d[1]), (m,i)=> {\n rankings[m[0]][i].push (d);\n });\n });\n\n return rankings;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2089,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":986,"value":"detection_rate = {\n return data_annotator (data);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2512,"value":" d3.median (_.map (_.filter (data, filter_EDS_pattern ([1,1,1,0,1,1], '')), (d)=>d.D_BUSTED_noS))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2620,"value":"genstats.wilcoxon (_.map (_.filter (data, filter_EDS_pattern ([1,1,1,0,1,1], '')), (d)=>d.D_S_noS), _.map (_.filter (data, filter_EDS_pattern ([1,1,1,1,1,1], '')), (d)=>d.D_S_noS))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2627,"value":"d3.median(_.map (_.filter (data, filter_EDS_pattern ([1,1,1,1,1,1], '')), (d)=>d.D_S_noS))","pinned":true,"hidden":false,"mode":"ojs"},{"id":2581,"value":"d3.median (_.map (_.filter (data, filter_EDS_pattern ([1,1,1,0,1,1], '')), (d)=>d.D_BUSTED_noS))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1507,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1690,"value":"set1 = _.map (_.filter (data, filter_EDS_pattern ([-1,-1,-1,-1,1,1], '')), (d)=>d.psi)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1695,"value":"set2 = _.map (_.filter (data, filter_EDS_pattern ([-1,-1,-1,-1,0,1], '')), (d)=>d.psi)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1442,"value":"_.filter (data, d=>d.classification && d.classification.has (\"Best\") && !d.classification.has (\"Averaged\") && d.best_model == '+S' && d.second_best == '+S+MH')","pinned":false,"hidden":false,"mode":"ojs"},{"id":1489,"value":"d3.median (_.map ( _.filter (data, d=>!d.classification || d.classification.size < 6), (d)=>Math.sqrt(d.omega3_MH) * d.p3_MH))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1412,"value":"[compute_aic_ranking[\"BUSTED\"][0].length + compute_aic_ranking[\"+S\"][0].length,compute_aic_ranking[\"+MH\"][0].length + compute_aic_ranking[\"+S+MH\"][0].length]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1236,"value":"sliced = _.filter (data, filter_EDS_pattern ([-1,-1,-1,-1,0,1], ''))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1277,"value":"filter_EDS_pattern = (pattern, best)=> { \n return (d)=> {\n if (d.best_model == best || best == \"\") {\n if (d.classification) {\n let keys = ['+S+MH', 'BUSTED','+S', '+MH','Averaged','Best'];\n let classed = true;\n _.each (keys, (k,i)=> {\n if (pattern[i] < 0) return;\n if (pattern [i])\n classed = classed && d.classification.has (k);\n else\n classed = classed && !d.classification.has (k);\n });\n return classed;\n }\n }\n \n return false;\n };\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1935,"value":"_.filter (_.filter (data, filter_EDS_pattern ([1,1,1,1,1,1],\"\")), (d)=>d[\"LRF_S\"] == 1 && d[\"delta\"] > 0)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1012,"value":"detection_sets = _.sortBy (extractSets(detection_rate), (d)=>-d.cardinality)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1962,"value":"_.filter (_.filter (data, filter_EDS_pattern ([0,-1,1,-1,-1,-1],\"\")), (d)=>d[\"LRF_S\"] == 1 && d[\"LRF_MH\"] == \"N/A\" && d[\"delta\"] > 0)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1112,"value":"datasetsByType = {\n let byType = {};\n _.each (detection_intersections, (d,k)=>{\n byType[d.name] = new Set (_.map (d.elems, (c)=>c.name));\n });\n return byType;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1118,"value":"extractFieldBySubset = (subset, field, censor)=> {\n censor = censor || 1e10;\n return _.filter (_.map ( _.filter (data, (d)=>subset.has (d.File)), (d)=>({'x' : d[field]})), (d)=>d.x <= censor);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2058,"value":"_.filter (_.filter (data, filter_EDS_pattern ([0,-1,1,-1,-1,-1,-1], \"\")), (d)=>d[\"LRF_S\"] == 1 && d[\"LRF_MH\"] == \"N/A\" && d[\"ma_pv\"] > 0.05)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1015,"value":"detection_intersections = _.sortBy (generateIntersections(detection_sets), (d)=>-d.cardinality)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1972,"value":"by_name = _.fromPairs (_.map (data, (d)=>[d.File, d]))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2004,"value":"unique_intersections = {\n let sects = [];\n _.each (detection_intersections, (d)=> {\n const ds = new Set (_.map (d.elems, (e)=>e.name));\n if (! _.some (sects, (e)=> {\n return e.elems.length == d.elems.length && e.elems.every((x) => ds.has(x.name));\n })) sects.push (d);\n });\n return sects;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1997,"value":"viewof support_table = Inputs.table (support_table_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1966,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1771,"value":"compute_p_and_q = (data, field, pc, qc)=> {\n pc = pc || 0.05;\n qc = qc || 0.10;\n var pv = _.sortBy (_.map (data, (d)=>d[field]));\n const N = pv.length;\n var qv = _.map (pv, (p,i)=> p * N / (i+1));\n\n let pN = -1, qN = -1;\n for (let i = 0; i < N && (pN < 0 || qN < 0); i++) {\n if (pN < 0 && pv[i] > pc) {\n pN = i;\n }\n if (qN < 0 && qv[i] > qc) {\n qN = i;\n }\n }\n return [pN/N,qN/N];\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1774,"value":"compute_p_and_q (data, \"pv_best\", 0.05, 0.20)","pinned":false,"hidden":false,"mode":"ojs"},{"id":25,"value":"data = await d3.csv (dataset.url,d3.autoType)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2659,"value":"_.groupBy (_.filter (addl_null_sims, (d)=>d.delta > .1 && d.p_ma == 1), d=>d.best)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2083,"value":"addl_null_sims = {\n data_annotator(kookish_null);\n let sims = [];\n _.each (kookish_null, (d)=> {\n const k = by_name[d.File.split ('_')[0]];\n let record = {};\n record.delta = k.delta;\n record.psi = k.psi;\n record.omega = 1;\n record.prop = k.p3_MH;\n record.p = d.p <= 0.05 ? 1 : 0;\n record.p_s = d.p_s <= 0.05 ? 1 : 0;\n record.p_MH = d.p_MH <= 0.05 ? 1 : 0 ;\n record.p_plain = d.p_plain <= 0.05 ? 1 : 0;\n record.p_ma = d.ma_pv <= 0.05 ? 1 : 0;\n record.best = d.best_model;\n record.aic_top2 = d.aic_top2;\n sims.push (record);\n });\n return sims;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2208,"value":"addl_power_sims = {\n data_annotator(kookish_power);\n let sims = [];\n _.each (kookish_power, (d)=> {\n const k = by_name[d.File.split ('_')[0]];\n let record = {};\n record.delta = k.delta;\n record.psi = k.psi;\n record.omega = k.omega3_MH;\n record.prop = k.p3_MH;\n record.p = d.p <= 0.05 ? 1 : 0;\n record.p_s = d.p_s <= 0.05 ? 1 : 0;\n record.p_MH = d.p_MH <= 0.05 ? 1 : 0 ;\n record.p_plain = d.p_plain <= 0.05 ? 1 : 0;\n record.p_ma = d.ma_pv <= 0.05 ? 1 : 0;\n sims.push (record);\n });\n return sims;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2197,"value":"_.map ([\"p_plain\", \"p_s\", \"p_MH\", \"p\", \"p_ma\"], (d)=>d3.sum (_.filter (addl_null_sims, (d)=>d.delta >= 0.15 && d.delta < 0.3), (c)=>c[d]) / _.filter (addl_null_sims, (d)=>d.delta >= 0.15 && d.delta < 0.3).length)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2212,"value":"_.map ([\"p_plain\", \"p_s\", \"p_MH\", \"p\", \"p_ma\"], (d)=>d3.sum (_.filter (addl_power_sims, (d)=>d.omega >= 4), (c)=>c[d]) / _.filter (addl_power_sims, (d)=>d.omega >= 4).length)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2075,"value":"kookish_null = await d3.csv (\"https://data.hyphy.org/web/busted-mh/enard-sims-null.csv\",d3.autoType)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2078,"value":"kookish_power = await d3.csv (\"https://data.hyphy.org/web/busted-mh/enard-sims-power.csv\",d3.autoType)","pinned":false,"hidden":false,"mode":"ojs"},{"id":31,"value":"contrastByGene = (data, field, pp) => {\n let result = {};\n _.each (data, (r)=> {\n const gene = r.File;\n if (! (gene in result)) {\n result[gene] = {};\n }\n _.each (field, (f) => {\n result[gene][f] = r[f];\n });\n if (pp) {\n pp (result[gene]);\n }\n });\n return _.chain (result).toPairs().map (d=>_.extend ({'gene' : d[0]}, d[1])).value();\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":626,"value":"extract_omega_distributions = (d)=> {\n let result = [];\n\n _.each ([\"BUSTEDS\",\"BUSTEDS-MH\"], (model)=> {\n _.each ([[\"w1\",\"p1\"],[\"w2\",\"p2\"],[\"w3\",\"p3\"]], (rate,i)=> {\n let record = {};\n record.gene = d.gene;\n record.type = model;\n record.value = d[model + \"|\" + rate[0]];\n record.weight = d[model + \"|\" + rate[1]];\n record.index = i;\n result.push (record);\n });\n });\n return result;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":265,"value":"binByGene = (data, p, aggregator, filter) => {\n p = p || 0.05;\n aggregator = aggregator || ((d)=>0);\n filter = filter || ((d)=>true);\n\n let result = [];\n _.each (data, (d)=> {\n let rec = {};\n rec.gene = File;\n if (filter (d)) {\n rec.ps = (d[\"p_s\"] <= p ? \"+\" : \"-\") + (d[\"p\"] <= p ? \"+\" : \"-\");\n aggregator (d, rec);\n result.push (rec);\n }\n });\n return result;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":380,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":148,"value":"twoByTwo = (m11,m12,m21,m22) => {\n const N = m11 + m12 + m21 + m22;\n const fmtP = d3.format (\".3p\");\n const formatP = (d)=>\"\" + d + \" (\" + fmtP (d/N) + \")\";\n return html`\n \n \n \n \n \n

	MH-	MH+	Total
SH-	${formatP(m11)}	${formatP(m12)}	${formatP(m11+m21)}
SH+	${formatP(m21)}	${formatP(m22)}	${formatP(m21+m22)}
Total	${formatP(m11+m21)}	${formatP(m12+m22)}	${N}

\n Cohen's κ = ${cohen_kappa (m11, m12, m21, m22)}\n `;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":247,"value":"cohen_kappa = (m11, m12, m21, m22) => {\n const N = m11 + m12 + m21 + m22; \n const p_0 = (m11 + m22) / N;\n const p_e = ((m11 + m12) * (m11 + m21) + (m21 + m22) * (m12 + m22)) / N / N;\n return (p_0 - p_e) / (1 - p_e);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":197,"value":"getCounts = (d,p)=> {\n p = p || 0.05;\n return [_.filter (d, (c)=>c[\"BUSTEDS|LRT p-value\"] >p && c[\"BUSTEDS-MH|LRT p-value\"] >p).length,\n _.filter (d, (c)=>c[\"BUSTEDS|LRT p-value\"] >p && c[\"BUSTEDS-MH|LRT p-value\"] <=p).length,\n _.filter (d, (c)=>c[\"BUSTEDS|LRT p-value\"] <=p && c[\"BUSTEDS-MH|LRT p-value\"] > p).length,\n _.filter (d, (c)=>c[\"BUSTEDS|LRT p-value\"] <=p && c[\"BUSTEDS-MH|LRT p-value\"] <= p).length];\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":407,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":693,"value":"plot_omega = (d, label)=> (\n {\n \"data\": {\n \"values\": d\n },\n \"width\": 200,\n //\"height\": 400,\n \"layer\" : [{\n \"mark\": {\n \"type\": \"circle\",\n \"opacity\": 0.8,\n \"stroke\": \"black\",\n \"strokeWidth\": 1\n },\n \"encoding\": {\n \"x\": {\n \"field\": \"value\",\n \"type\": \"quantitative\",\n \"axis\": {\"grid\": false, \"title\" : label ? label : false, \"titleFontSize\" : 14, \"tickCount\" : 5},\n \"scale\" : {\"type\" : \"symlog\"}\n },\n \"color\" : {\"value\" : \"darkgrey\"},\n \"size\": {\n \"field\": \"weight\",\n \"type\": \"quantitative\",\n \"title\": \"Proportion\",\n \"legend\": false,//{\"clipHeight\": 50, \"orient\": \"top\"},\n \"scale\": {\"rangeMax\": 400}\n },\n }},{\n \"mark\": {\n \"type\": \"rule\",\n \"color\": \"red\",\n \"strokeWidth\": \"2\",\n },\n \"encoding\": {\n \"x\": {\n \"datum\": {\"expr\": \"1\"},\n \"type\": \"quantitative\",\n }\n }\n }\n \n \n ],\n \"config\": {\n \"style\": {\n \"cell\": {\n \"stroke\": \"transparent\"\n }\n }\n }\n}\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":65,"value":"vegalite = require (\"vega-embed\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":963,"value":"genstats = require('https://bundle.run/genstats@0.0.1')","pinned":false,"hidden":false,"mode":"ojs"},{"id":1003,"value":"import {extractSets, UpSetJSElement, generateIntersections} from \"@sgratzl/upset-js\"","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W35","stdlib":"1","titling":"auto"}