31:T4c8,viewof detection_plot = Plot.plot({ style: {"fontSize" : 14, "fontSize-swatches" : 14, "fontFamily" : "Helvetica"}, marginBottom: 40, marginTop: 30, marginLeft : 50, width : 600, height: 600, y: { grid: true, tickFormat: "f", label: "Relative rate in foreground", "type" : "log", "exponent" : 1., ticks :5, }, x: { grid: true, tickFormat: "f", label: "Relative rate in background", "type" : "log", "exponent" : 1., ticks: 4 }, color: { legend: true, "type" : "linear", label: "-log10 (q-value)", scheme: 'rdpu', reverse: false }, marks: [ Plot.ruleY([0]), Plot.ruleX([0]), Plot.line([{'x' : 0.01, 'y': 0.01},{'x' : 100, 'y': 100}], {x: "x", y: "y", "stroke" : "#CCC"}), //Plot.rect([{'x1' : 0.9, 'y1': 0.9, 'x2' : 1, 'y2': 1.}], {'x1' : 'x1', 'y1': 'y1', 'x2' : 'x2', 'y2': 'y2', opacity : 0.2}), Plot.dot(_.filter (sim_data, (d)=>d.FDR <= maxq), {x: "bg", y: "fg", fill: (d)=>-Math.log10 (Math.max (1e-16, d["FDR"]), 10), r : (d)=>d.ratio > 1 ? d.ratio : 1/d.ratio, opacity : 0.7, stroke : "black"}), Plot.dot(_.filter (sim_data, (d)=>d.FDR <= maxq), Plot.pointer({x: "bg", y: "fg", fill: "red"})), ] })32:[] 2f:{"title":"RER-hyphy for mammalian mole data","cells":[{"id":0,"value":"# RER-hyphy for mammalian mole data","pinned":false,"hidden":false,"mode":"md"},{"id":298,"value":"viewof maxq = Inputs.range([0, 1], {label: \"FDR q-value\", step: 0.01, value : 0.05})","pinned":false,"hidden":false,"mode":"ojs"},{"id":317,"value":"** Figure 1** Relative amino-acid rates (using a genome-average tree as a reference) for foreground (subterranean mammals) and background (all else) branches in the tree for individual genes. Points above the diagonal are accelerated on FG relative to BG. The color of each dot shows the FDR-corrected q-value (as -log₁₀ (q)) for the rates being different between FG and BG. The size of the bubble is proportional to `max [FG/BG, BG/FG]`. Mouse-over and click on individual data circles (genes), to see more details and open up detailed result pages.","pinned":false,"hidden":false,"mode":"md"},{"id":344,"value":"detection_plot ? md`Gene ${detection_plot.gene}. Relative rates : FG ${detection_plot.fg.toFixed (2)}, BG ${detection_plot.bg.toFixed (2)}. q-value ${detection_plot.FDR}. Detailed results` : md`Select a bubble to view more details`","pinned":false,"hidden":false,"mode":"ojs"},{"id":27,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":323,"value":"Table 1. Detailed gene by gene results","pinned":false,"hidden":false,"mode":"md"},{"id":435,"value":"viewof search_results = Inputs.search (sim_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":325,"value":"viewof results = Inputs.table (sim_data, {\n format :{\n \"gene\" : (d)=>html`${d}`\n },\n columns: ['gene','fg','bg','ratio','branch','alternative','null','Proportional:Proportional Partitioned p-val', 'Proportional:Proportional Partitioned LRT','Proportional:Unconstrained Test p-val', 'Proportional:Unconstrained Test LRT', 'alternative branch LRT', 'null branch LRT'],\n header : {\n \"gene\" : \"Gene\",\n \"fg\" : \"FG rel. rate\",\n \"bg\" : \"BG rel. rate\",\n \"ratio\" : \"FG/BG ratio\",\n \"p\" : \"p-value FG = BG\",\n \"FDR\" : \"q-value FG = BG\",\n \"B\" : \"# branches\"\n }\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":482,"value":"viewof gene_id = Inputs.select(only_search_results, {label: \"Show this gene:\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":579,"value":"viewof ind_branch = Inputs.table (branch_pvals)","pinned":false,"hidden":false,"mode":"ojs"},{"id":628,"value":"gene_id","pinned":true,"hidden":false,"mode":"ojs"},{"id":397,"value":"urls = ({'Mole' : \"https://data.hyphy.org/web/rer/subterranean_060724/\",\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":410,"value":"suffix = ({'Mole' : \".RER.json.gz\",\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":604,"value":"summary_file = 'summary-lrt.csv'","pinned":false,"hidden":false,"mode":"ojs"},{"id":402,"value":"scenario = \"Mole\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"sim_data = {\n let pvalue_data = await d3.csv (urls[scenario] + summary_file, d3.autoType); \n const pvalue_column = 'Proportional:Proportional Partitioned p-val';\n let rd = _.sortBy (_.map (_.filter (pvalue_data, (d)=>_.isNumber (_.get (d, pvalue_column))), (d)=>d), (d)=>d[pvalue_column]);\n _.each (rd, (d,i)=> {\n d[\"FDR\"] = d[pvalue_column]*rd.length/(i+1);\n try {\n let nulls = _.map (d.null.split (\",\"), e=>+e);\n let alts = _.map (d.alternative.split (\",\"), e=>+e);\n let BC = _.filter (nulls, (e,i)=> {\n return e <= 0.05 && alts[i] <= 0.05;\n });\n d[\"B\"] = BC.length;\n } catch {}\n //let alts = _.map (d.alternative.split (\",\"), e=>+e);\n });\n return rd;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":484,"value":"only_search_results = {\n var data = []\n for(var i = 0;i< search_results.length;i++){\n data.push(search_results[i][\"gene\"])\n }\n return data\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":535,"value":"rer_results_json = await get_json(results_file)","pinned":false,"hidden":false,"mode":"ojs"},{"id":559,"value":"branch_pvals = _.map(_.entries(rer_results_json['branch level analysis']), ([key, d]) => {\n return {\n 'Branch': key,\n 'Single branch (null)': d['null']['p-value'],\n 'All but this branch (alternative)': d['alternative']['p-value']\n };\n});","pinned":true,"hidden":false,"mode":"ojs"},{"id":552,"value":"pako = require('pako@2.1.0/dist/pako.min.js')","pinned":false,"hidden":false,"mode":"ojs"},{"id":498,"value":"get_json = async (json_source)=> {\n if (json_source) {\n if (json_source.substr (json_source.length-3) == \".gz\") {\n return JSON.parse (pako.inflate(await d3.buffer(json_source), { to: 'string' }));\n }\n return d3.json (json_source);\n try {\n return d3.json (json_source);\n } catch {}\n //results_file.json();\n }\n try {\n return JSON.parse (pako.inflate(await results_file.arrayBuffer(), { to: 'string' }));//results_file.json();\n } catch {}\n return results_file.json();\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":523,"value":"results_file = urls[scenario] + gene_id + suffix[scenario]","pinned":false,"hidden":false,"mode":"ojs"},{"id":637,"value":"b_pvals = {\n let chosen_gene = _.filter(pvalue_data, d=> d.gene === gene_id )[0]\n let branch_list = chosen_gene['branch'].split (\",\")\n let null_list = chosen_gene['null'].split (\",\")\n let alt_list = chosen_gene['alternative'].split(',')\n let to_return = []\n /*for (let i = 0; i < branch_list.length; i++) {\n let to_concat = {Branch: branch_list[i], 'Single branch (null)':null_list[i], 'All but this branch (alternative)' : alt_list[i]}\n to_return.push(to_concat)\n }\n return to_return */\n return _.map(branch_list, (branch, i) => ({\n Branch: branch,\n 'Single branch (null)': null_list[i],\n 'All but this branch (alternative)': alt_list[i],\n}));\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":621,"value":"pvalue_data = await d3.csv (urls[scenario] + summary_file, d3.autoType)","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}