30:Tfb9,loaderParagraph = { let params = new URLSearchParams(location.search); let variant_url = params.get("variants"); let meta_url = params.get("meta"); let attr_url = params.get("attribution"); let title = params.get("title") || "COG-UK"; let loader = html`

Loading variant data...

`; loader.value = null; yield loader; let rd = await obtainSourceData( null, variant_url || "https://data.hyphy.org/web/SARS-CoV-2/variants.json.gz", false, true ); let column_map = { Sample: 0, AF: 1, variant_keys: 2 }; let variant_key = { POS: 0, REF: 1, ALT: 2, EFFECT: 3, CODON: 4, TRID: 5, AA: 6 }; rd.top_cols = _.size(column_map); rd.inner_cols = _.size(variant_key); loader = html`

Loading metadata...

`; loader.value = null; yield loader; let an = await obtainSourceData( null, meta_url || "https://data.hyphy.org/web/SARS-CoV-2/meta.tsv.gz", true ); loader = html`

Performing variant error filtering

`; yield loader; let cbp = _.map(_.range(29903), (d) => 0); let afc = column_map["AF"]; let var_key = column_map["variant_keys"]; let posc = variant_key["POS"]; for (let i = 0; i < rd.values.length; i += rd.top_cols) { if ( rd.keys[afc][rd.values[i + afc]] >= 0.1 && rd.keys[afc][rd.values[i + afc]] <= 0.25 ) { const var_position = rd.variant_keys[posc][ rd.keys[var_key][rd.values[i + var_key] * rd.inner_cols + posc] ]; cbp[var_position] += 1; //pos.push (var_position); } } let bySiteCount = _.chain(cbp) .countBy() .toPairs() .map((d) => { return { samples: +d[0], count: d[1] }; }) .value(); let singleLambda = d3.sum(cbp) / cbp.length; let error_rate = singleLambda / 29903; let singlePoission = _.find( _.map( _.filter( poissonSupport( singleLambda, _.map(bySiteCount, (d) => d.samples), cbp.length ), (d) => d.count > 0.1 ), (d, i) => { return [i, (d.count - bySiteCount[i].count) / d.count]; } ), (d) => d[1] < -1 ); let keep_in = {}; for (let i = 0; i < rd.values.length; i += rd.top_cols) { let vk = make_variant_key_long_encoded( rd.keys[var_key], rd.values[i + var_key] * rd.inner_cols, variant_key ); if (vk in keep_in) { keep_in[vk] += 1; } else { keep_in[vk] = 1; } } let before = rd.rows; //singlePoission[0] = 2; if (singlePoission[0] > 1) { let filtered_array = []; for (let i = 0; i < rd.values.length; i += rd.top_cols) { let vk = make_variant_key_long_encoded( rd.keys[var_key], rd.values[i + var_key] * rd.inner_cols, variant_key ); if (keep_in[vk] >= singlePoission[0]) { for (let j = 0; j < rd.top_cols; j += 1) { filtered_array.push(rd.values[i + j]); } } } rd.values = filtered_array; rd.rows = rd.values.length / rd.top_cols; } loader = html`

Rendering the dashboard

`; yield loader; let attributions = await d3.tsv( attr_url || "https://raw.githubusercontent.com/usegalaxy-eu/sars-cov-2-processing-requests/main/CONTRIBUTORS.tsv" ); let retValue = md`### Results computed using the [global platform for SARS-CoV-2 analysis](https://covid19.galaxyproject.org/genomics/global_platform/) Poisson modeling estimated the global error rate of ${floatFmt( error_rate )}/base; ${before - rd.rows} allelic variants (AV) occurring in fewer than ${ singlePoission[0] } samples are deemed to be unreliable and have been removed. `; retValue.value = [rd, an, title, attributions, column_map, variant_key]; yield retValue; }31:T555,html`

${results.samples} samples analyzed	${results.unique_variants} unique allelic variants (AV)	${floatFormat(results.per_sample)} AV per sample
${floatFormat(results.fixed_per_sample)} fixed AV per sample	${floatFormat(results.lf_per_sample)} low frequency AV per sample	${floatFormat(results.syn_per_sample)} : ${floatFormat(results.nonsyn_per_sample)} mean Syn : mean Non-Syn per sample

`32:Tc3b,fig2=vegalite ({ "$schema": "https://vega.github.io/schema/vega-lite/v4.json", "vconcat" : [{ "data": { "values": variantToViewDetails }, "layer" : [ { "title" : "Allele frequency distribution across samples where this AV is present", "width": 800, "height": 80, "transform":[{ "density": "AF", //"bandwidth": 0.01 }], "mark": {type: "area", "opacity" : 0.2, tooltip : true, line : true}, "encoding": { "x": { "field": "value", "grid" : null, "title": "Allele Frequency", "type": "quantitative", "axis": {"grid": false, "titleFontSize" : 14} }, "y": { "field": "density", "type": "quantitative", "title" : "", "axis": {"grid": false} }, "color" : {"value" : "grey"}, } }, { "mark": {type: "tick", "opacity" : 0.5, size : 10, thickness: 2}, "transform":[{ "calculate": "-0", "as": "placement" }], "encoding": { "tooltip": [ {"field": "AF", "type": "quantitative"}, {"field": "Sample", "type": "nominal"} ], "x": { "field": "AF", "grid" : null, "title": "Allele Frequency", "type": "quantitative", "axis": {"grid": false} }, "y" : { "type": "quantitative", "field" : "placement" }, "color" : {"value" : "darkred"}, } }, ]}, { "title" : "Temporal AV dynamics", "resolve": {"scale": {"y": "independent"}}, "width": 800, "height": 160, "data" : {values : temporalVariantDynamics}, "encoding": { "x": {"field": "date", "type": "temporal", "title": "Sample collection date", "axis" : {"grid" : false, "titleFontSize" : 14, "format": "%Y/%m/%d"}}, }, "layer": [ { "mark": {"stroke": "black", "color" : "black", "type": "area", "interpolate": "step-after", "opacity" : 0.4}, "encoding": { "y": {"field": "fraction", "title": "Sample fraction", "type": "quantitative", "axis" : {"grid" : false, "titleFontSize" : 14}} } }, { "mark": {"type": "line", "opacity": 0.5, "point": true, "size": 3, "interpolate" : "step-after"}, "encoding": { "y": {"field": "mean", "title": "Mean AF", "type": "quantitative", "axis" : {"grid" : false, "titleFontSize" : 14, "titleColor" : "firebrick"}, }, "tooltip": [ {"field": "date", "type": "temporal"}, {"field": "mean", "type": "quantitative"} ], "color" : {"value" : "firebrick"}, } }, ]} ] })33:Tc40,results = { let s = { variants : null, 'samples' : null, 'meta' : null }; if (loaderParagraph.value) { //s.data = _.filter (loaderParagraph.value[0], (r)=>metaData[r.Sample]>=date_range.range[0] && metaData[r.Sample]<=date_range.range[1]); s.selected = []; let vals = loaderParagraph.value[0].values; let cols = loaderParagraph.value[0].top_cols; let inner_cols = loaderParagraph.value[0].inner_cols; let colIdx = loaderParagraph.value[4]; let innerIdx = loaderParagraph.value[5]; let sampleID = colIdx["Sample"]; let AF = colIdx["AF"]; let vk = colIdx ["variant_keys"]; let EFFECT = innerIdx["EFFECT"]; for (let i = 0; i < vals.length; i+=cols) { let sample_date = metaData[loaderParagraph.value[0].keys[sampleID][vals[i + sampleID]]]; if (sample_date >= date_range.range[0] && sample_date <= date_range.range[1]) { s.selected.push (i); } } s.meta = metaData; s.variants = s.selected.length; s.bySample = new Object(); let kindPerSample = new Object(); for (let i = 0; i < s.selected.length; i++) { let my_sample = vals[s.selected[i] + sampleID]; if (!(my_sample in s.bySample)) { s.bySample [my_sample] = []; kindPerSample[my_sample] = [0,0,0,0]; } let myAF = loaderParagraph.value[0].keys[AF][vals[s.selected[i] + AF]]; let myEffect = loaderParagraph.value[0].keys[vk][(vals[s.selected[i] + vk])*inner_cols+EFFECT]; myEffect = loaderParagraph.value[0].variant_keys[EFFECT][myEffect]; if (myAF >= 0.75) kindPerSample[my_sample][0] ++; else if (myAF <= 0.25) kindPerSample[my_sample][1] ++; if (myEffect == "NON_SYNONYMOUS_CODING") kindPerSample[my_sample][2] ++; else if (myEffect == "SYNONYMOUS_CODING") kindPerSample[my_sample][3] ++; s.bySample [my_sample].push (s.selected[i]); } s.byVariant = new Object(); s.annotations = new Object(); for (let i = 0; i < s.selected.length; i++) { let variant_code = make_variant_key_long_encoded (loaderParagraph.value[0].keys[vk], vals[s.selected[i]+vk] * inner_cols, innerIdx); if (!(variant_code in s.byVariant)) { s.byVariant [variant_code] = []; } s.byVariant [variant_code].push (s.selected[i]); s.annotations [variant_code] = annotate_variant (vk, vals[s.selected[i]+vk] * inner_cols, innerIdx); } /*s.extendedVariants = new Array (); for (let i in s.byVariant) { const recoded = recode_variant (i, colIdx); s.extendedVariants.push (recoded); } s.extendedVariants = _.chain (s.extendedVariants)*/ s.samples = _.size (s.bySample); s.unique_variants = _.size (s.byVariant); s.per_sample = s.variants / s.samples; s.fixed_per_sample = d3.mean (_.map (kindPerSample, (d)=>d[0])); s.lf_per_sample = d3.mean (_.map (kindPerSample, (d)=>d[1])); s.syn_per_sample = d3.mean (_.map (kindPerSample, (d)=>d[3])); s.nonsyn_per_sample = d3.mean (_.map (kindPerSample, (d)=>d[2])); } return s; }34:T466,temporalVariantDynamics = { let vd = variantKeyList[1]; if (vd) { vd = results.byVariant[vd[variantToView]]; const SAMPLE = loaderParagraph.value[4]["Sample"], AF = loaderParagraph.value[4]["AF"]; let lookup = {}; _.each (vd, (d)=>lookup[loaderParagraph.value[0].keys[SAMPLE][loaderParagraph.value[0].values[d+SAMPLE]]] = loaderParagraph.value[0].keys[AF][loaderParagraph.value[0].values[d+AF]]); let included = {}; let observed = _.chain (_.groupBy (_.map (lookup, (v,k)=> {return {'date' : results.meta[k], 'AF' : v}}), (d)=>d.date ? d.date.getTime(): null)).toPairs().map ((d)=>{included[parseInt(d[0])] = 1; return {'date': parseInt(d[0]), 'fraction' : d[1].length/samplesByDate[parseInt(d[0])], 'mean' : d3.mean (d[1], (s)=>s.AF), 'median' : d3.median(d[1], (s)=>s.AF)};}).value(); _.each (samplesByDate, (count, date)=> { if (((+date) in included) == false) { observed.push ({ 'date' : +date, 'fraction': 0, 'mean' : 0, 'median' : 0 }); } }); return observed; } return []; }35:Taeb,variantTableData = (variants, selector, record_samples)=> { let variantsPresent = _.map (selector, d => []); let map_to_selector = { }; _.each (selector, (s, i)=> { _.each ([...s[3]], (p)=>map_to_selector [p] = i); }); if (selector.length == 0) { return [{"var" : "Select a set of mutations to track"}]; } //return map_to_selector; const SAMPLE = loaderParagraph.value[4]["Sample"], AF = loaderParagraph.value[4]["AF"], POS = loaderParagraph.value[5]["POS"], VK = loaderParagraph.value[4]["variant_keys"], VD = loaderParagraph.value[0]; let haz = {}; _.each (variants, (v)=> { _.each (v, (r)=> { let myPOS = VD.variant_keys[POS][VD.keys[VK][VD.values[r+VK]*VD.inner_cols + POS]]; if (myPOS in map_to_selector) { let add_me = false; let i = map_to_selector[myPOS]; let vr = selector[i]; let myPattern = results.annotations [make_variant_key_long_encoded (VD.keys[VK], VD.values[r+VK]*VD.inner_cols, loaderParagraph.value[5])]; if (myPattern) { if (_.isArray (vr[4])) { if (vr[4].length == 2) { if (_.isArray (myPattern)) { if (myPattern.length == 2) { add_me = myPattern[0] == vr[4][0] && myPattern[1] == vr[4][1]; } } } else { if (vr[4].length == 1) { add_me = _.isArray (myPattern) && myPattern[0] == vr[4][0]; } else { add_me = _.isArray (myPattern) && myPattern.length == 0; } } } else { if (_.isNumber (vr[4])) { add_me = myPattern && myPattern == vr[4]; } } } if (add_me) { variantsPresent[i].push ([VD.keys[SAMPLE][VD.values[r + SAMPLE]], VD.keys[AF][VD.values[r + AF]], make_variant_key(r)]); } } }); }); return _.map (selector, (v, i)=> { let r = { 'var' : v[2] + "/" + v[1], 'count' : variantsPresent[i].length, 'mean' : [d3.mean (variantsPresent[i], (d)=>d[1]), d3.quantile (variantsPresent[i], 0.025, (d)=>d[1]), d3.quantile (variantsPresent[i], 0.975, (d)=>d[1])], 'fixed' : _.filter (variantsPresent[i], (d)=>d[1] >= 0.75).length, 'low' : _.filter (variantsPresent[i], (d)=>d[1] <= 0.25).length, 'variants' : new Set (_.uniqBy(_.map (variantsPresent[i], (d)=>d[2]))) }; if (record_samples) { r['samples'] = _.map (variantsPresent[i], (d)=>d[0]); } return r; }); }36:T651,voc = { let voc = await d3.text ("https://raw.githubusercontent.com/veg/SARS-CoV-2/compact/intrahost/voc.tsv"); voc = _.mapValues (_.groupBy (d3.tsvParseRows (voc), (d)=>d[0]), (v)=>_.sortBy (_.map (v, (r)=>[r[0],r[1],(+r[2])+1, new Set ([(+r[2])+1, (+r[2])+2, (+r[2])+3])]), (r)=>r[2])); voc = _.mapValues (voc, (values)=> { _.each (values, (row) => { let pieces = null; row[1].replace(/^([A-Z])[0-9]+([A-Z])$/, (m,from,to)=> { pieces = [from,to]; }); if (pieces && pieces.length == 2) { row.push (pieces); return; } row[1].replace(/^([A-Z])[0-9]+$/, (m,from)=> { pieces = [from]; }); if (pieces && pieces.length == 1) { row.push (pieces); return; } row[1].replace(/^([A-Z])[0-9]+stop+$/, (m)=> { pieces = []; }); if (pieces && pieces.length == 1) { row.push (pieces); return; } row[1].replace(/^^del([0-9]+)$/, (m,len)=> { pieces = +len; _.each ([...row[3]], (p)=>{ for (var i = len; i > 0; i-=3) { row[3].add (p-i+1); } }); }); if (pieces && pieces.length == 1) { row.push (pieces); return; } row.push (pieces); }); return values; }); voc [""] = []; return voc; }37:T53a,make_spatial_clusters = (binner, coord, f,t, src)=>{ if (loaderParagraph.value) { const VD = loaderParagraph.value[0]; f = f || af_range[0]; t = t || af_range[1]; const POS = loaderParagraph.value[5]["POS"], AF = loaderParagraph.value[4]["AF"], VK = loaderParagraph.value[4]["variant_keys"], EFFECT = loaderParagraph.value[5]["EFFECT"]; const get_effect = (i)=> { return VD.variant_keys[EFFECT][VD.keys[VK][VD.values[i+VK]* VD.inner_cols + EFFECT]]; }; let spatialClusters = _.groupBy (_.toPairs(src), (d)=>binner (VD.variant_keys[POS][d[0].split('|')[0]])); return _.flatten (_.map (spatialClusters, (d,k)=> { let passingFilter = _.filter (d, (v)=> _.every (v[1], (vr)=>{ const myAF = VD.keys[AF][VD.values[vr+AF]]; return myAF >= f && myAF<= t; })); let byVariant = _.mapValues (_.groupBy (passingFilter, (v)=>map2key (get_effect(v[1][0]))), (v)=>d3.sum(v, (r)=>r[1].length)); return _.map (byVariant, (v,t)=> {return { 'coord' : coord (k), 'count' : parseInt(v), 'kind' : t, 'AF' : d3.mean (_.filter (passingFilter, (v)=>map2key (get_effect(v[1][0])) == t), (v)=>VD.keys[AF][VD.values[v[1][0]+AF]]) }}); })); } return []; }38:T820,function multiAutoSelect(config = {}) { const { value, title, description, disabled, autocomplete = "off", placeholder, size, options, list = "variants" } = Array.isArray(config) ? { options: config } : config; const optionsSet = new Set(options); const form = input({ type: "text", title, description, attributes: { disabled }, action: fm => { const addSelectedOption = d => { const ele = html`${d} `; ele.querySelector("button").addEventListener("click", b => { fm.value.splice(fm.value.indexOf(d), 1); renderSelection(); fm.dispatchEvent(new CustomEvent("input")); fm.input.focus(); }); return ele; }; function renderSelection() { fm.output.innerHTML = ""; for (let o of fm.value) { fm.output.appendChild(addSelectedOption(o)); } } fm.input.value = ""; fm.value = value || []; fm.onsubmit = e => e.preventDefault(); fm.input.oninput = function(e) { e.stopPropagation(); if ( optionsSet.has(fm.input.value) && fm.value.indexOf(fm.input.value) === -1 ) { fm.value.push(fm.input.value); renderSelection(); fm.dispatchEvent(new CustomEvent("input")); fm.input.value = ""; } }; renderSelection(); }, form: html` ` }); form.output.style["margin-left"] = "0px"; return form; }39:Td4d,html` `3a:[] 2e:{"title":"Intrahost allelic variant SARS-CoV-2 analysis for Estonian samples","cells":[{"id":0,"value":"md`# Intrahost allelic variant SARS-CoV-2 analysis for ${loaderParagraph.value?loaderParagraph.value[2]:\"...\"} samples`","pinned":false,"hidden":false,"mode":"ojs"},{"id":932,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":1524,"value":"md`All result processing takes place in the browser. \nYou can select a date range to restrict the analysis to using the widget below. Current date range : ${timeFmt(date_range.range[0])} - ${timeFmt(date_range.range[1])}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1499,"value":"viewof date_range = rs(samplesForSlider, d=>d.date, value=>d3.sum(value.values.map(d=>d.count)), {height: 140, yTicks:2,yScale:d3.scalePow().exponent(0.5),rangeFmt : (a,b)=>\"Recompute for \" + timeFmt(a) + \" : \" + timeFmt (b)})","pinned":false,"hidden":false,"mode":"ojs"},{"id":592,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":538,"value":"fig1label=md`
\n### Allelic variant (AV) density by genomic region and type.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1174,"value":"md`The plot below shows normalized allelic variant density (variants per kilobase/per sample), with AVs stratified by type. A density of 5 would mean that in an average sample, 5 of allelic variants occur per kilobase. The plot is restricted to AVs whose allelic frequencies are between ${af_range[0]} and ${af_range[1]} for **all** samples where they occur: a total of ${d3.sum (spatialVariantDensityByGene, (d)=>d.count)} variants` ","pinned":false,"hidden":false,"mode":"ojs"},{"id":1064,"value":"viewof af_range = rangeSlider({\n title: 'Allele frequency range to include in the plot',\n min: 0.05,\n max: 1.,\n value: [0.05, 1.0],\n color: 'hsl(20, 100%, 40%)',\n format: '.0%',\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1056,"value":"fig1=vegalite ({\n \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.json\",\n \"data\": { \"values\": _.filter (spatialVariantDensityByGene, (d)=>d.kind != \"Non-coding\")},\n \"mark\": {\"type\" : \"circle\", \"tooltip\" : {\"content\" : \"data\"}},\n \"width\" : 600,\n \"height\" : 120,\n \"encoding\": {\n \"y\": {\n \"field\": \"kind\",\n \"type\": \"ordinal\",\n \"title\" : \"AV\",\n //\"timeUnit\": \"day\",\n },\n \"x\": {\n \"field\": \"coord\",\n \"type\": \"ordinal\",\n \"sort\": _.map (gene_coordinates, (d)=>d[1]),\n \"axis\" : {title : null}\n //\"timeUnit\": \"hours\"\n },\n \"size\": {\n \"field\": \"density\",\n \"type\": \"quantitative\",\n \"legend\" : {\n \"title\" : \"Variant count per Kb/per sample\",\n \"orient\": \"top\"\n }\n },\n \"color\": {\n \"field\": \"AF\",\n \"type\": \"quantitative\",\n \"title\": \"Mean AF\",\n \"scale\": {\n \"scheme\": \"orangered\"\n }\n },\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":577,"value":"fig2_label=md`### View a specific AV\n\nSelect a specific allelic variants by looking it up via its nucleotide genomic coordinate (e.g. \\`23403\\`), gene and amino-acid substitutions (e.g. \\`S|N501Y\\`), or codon change (e.g. \\`TTT/ATT\\`).\n\nThe top panel shows the distribution of AF for this AF among the samples where it is found. The bottom panel shows temporal dynamics of mean allele frequencies, and the fraction of samples where this AV was found. \n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1108,"value":"viewof variantToView = autoSelect({\n options: variantKeyList[0],\n title: \"Select an intra-host variant to explore further [genomic coordinate, change, annotation]\",\n value: \"23403 A>G S|D614G gAt/gGt\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1131,"value":"md`Variant ${variantToView} is found in **${variantToViewDetails.length}/${results.samples}** samples.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1122,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1640,"value":"md`### Variants of concern report`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1692,"value":"md`Display how often specific mutations occur in the samples` ","pinned":false,"hidden":false,"mode":"ojs"},{"id":1695,"value":"viewof vocSet = select ({\n options: _.sortBy (_.keys (voc)),\n description: \"Use this set of variants\",\n value: \"\"\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":1679,"value":"viewof use_frac = checkbox ({\n options: [{ value: \"toggle\", label: \"Use fractions of total\" }],\n value: \"toggle\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1658,"value":"table (forTable,\n {\n limit: 5000,\n maxHeight: 1000,\n enableCSVDownload: true,\n sort: true,\n enableFilter: false,\n columns: [\n {\n key: 'var',\n name: 'AV',\n },\n {\n key : 'count',\n name : 'Prevalence',\n render: (val)=>float_format (val)\n },\n {\n key : 'mean',\n name : 'Allele frequency
mean (2.5%-97.5%)',\n render: (val)=>val ? float_formatNA (val[0]) + \" (\" + float_formatNA (val[1]) + \" - \" + float_formatNA (val[2]) + \")\" : \"N/A\"\n },\n {\n key : 'fixed',\n name : 'Prevalence AF≥75%',\n render: (val)=>float_format (val)\n },\n {\n key : 'low',\n name : 'Prevalence AF≤25%',\n render: (val)=>float_format (val)\n } \n ]\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":1903,"value":"md`### Acknowledgements`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1881,"value":"acknF(loaderParagraph.value)","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1035,"value":"md`#### Code and libraries`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1661,"value":"float_format = (v)=> {\n return use_frac ? floatFormat (v/results.samples) : v;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1954,"value":"float_formatNA = (v)=> {\n if (_.isUndefined (v)) return \".\";\n return floatFormat (v);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1026,"value":"make_variant_key = (v)=> {\n return v.POS + \"|\" + v.REF + \"|\" + v.ALT;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1112,"value":"make_variant_key_long = (v)=> {\n return \"\" + v[0] + \" \" + v[1] + \">\" + v[2] + (v[3] != \".\" ? \" \" + v[3] + \"|\" + v[4] : \"\") + (v[5] != \".\" ? \" \" + v[5] : \"\");\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1952,"value":"make_variant_key_long_encoded = (v, offset, index)=> {\n return \"\" + v[offset + index[\"POS\"]] + \"|\" + v[offset + index[\"REF\"]] + \"|\" + v[offset + index[\"ALT\"]] + \"|\" + v[offset + index[\"TRID\"]] + \"|\" + v[offset + index[\"AA\"]] + \"|\" + v[offset + index[\"CODON\"]];\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1951,"value":"recode_variant = (v, index) => {\n v = _.map (v.split (\"|\"), (d)=>+d);\n return _.map ([\"POS\",\"REF\",\"ALT\",\"TRID\",\"AA\",\"CODON\"], (k,i)=> {\n return loaderParagraph.value[0].variant_keys[index[k]][v[i]];\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1950,"value":"make_variant_key_encoded = (v, offset, index)=> {\n return \"\" + v[offset + index[\"POS\"]] + \"|\" + v[offset + index[\"REF\"]] + \"|\" + v[offset + index[\"ALT\"]];\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1508,"value":"metaData = {\n if (loaderParagraph.value) {\n let samples = new Set (loaderParagraph.value[0].keys[loaderParagraph.value[4][\"Sample\"]]);\n let m = _.fromPairs(_.map (_.filter (loaderParagraph.value[1], (d)=>samples.has (d.run_accession)) , (d)=>[d.run_accession, d.collection_date]));\n return m;\n }\n return [];\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":952,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":1947,"value":"variantToViewDetails = \n{ \n if (loaderParagraph.value) {\n const SAMPLE = loaderParagraph.value[4][\"Sample\"],\n AF = loaderParagraph.value[4][\"AF\"];\n \n return _.map (variantKeyList[1] ? results.byVariant[variantKeyList[1][variantToView]] : [], (d)=> {\n return {\n \"Sample\" : loaderParagraph.value[0].keys[SAMPLE][loaderParagraph.value[0].values[d+SAMPLE]],\n \"AF\" : loaderParagraph.value[0].keys[AF][loaderParagraph.value[0].values[d+AF]]\n }\n });\n }\n return [];\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1946,"value":"variantKeyList = {\n if (results.byVariant) {\n let extendedVariants = new Array ();\n for (let i in results.byVariant) {\n const recoded = recode_variant (i, loaderParagraph.value[5]);\n extendedVariants.push ([recoded,i]);\n }\n extendedVariants = _.chain (extendedVariants).sortBy ((d)=>d[0][0]).map ((d)=>[make_variant_key_long(d[0]), d[1]]).value();\n return [_.map (extendedVariants, (d)=>d[0]), _.fromPairs (extendedVariants)];\n }\n return [];\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1302,"value":"samplesByDate = {\n if (loaderParagraph.value) {\n const SAMPLE = loaderParagraph.value[4][\"Sample\"];\n return _.countBy (_.map (results.bySample, (d,k)=>{\n let mySample = loaderParagraph.value[0].keys[SAMPLE][k];\n return results.meta[mySample] ? results.meta[mySample].getTime() : null;\n }));\n }\n return {};\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1506,"value":"samplesForSlider = _.map (_.countBy (_.toPairs(metaData), (d)=>d[1].getTime()), (v,k)=>{return {'date' : new Date(+k), 'count' : v}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1136,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":1454,"value":"forTable = variantTableData (results.bySample, voc[vocSet])","pinned":false,"hidden":false,"mode":"ojs"},{"id":1383,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":1424,"value":"annotate_variant = (vk, index, colidx)=>{\n let row = _.map ([\"EFFECT\",\"REF\",\"ALT\",\"AA\"], (d)=> {\n let idx = colidx[d];\n return loaderParagraph.value[0].variant_keys[idx][loaderParagraph.value[0].keys[vk][index+idx]];\n });\n\n \n\n let pattern = null;\n \n if (row[0] == \"NON_SYNONYMOUS_CODING\") {\n if (row[1].length == 1 && row[2].length == 1) {\n row[3].replace(/^([A-Z])[0-9]+([A-Z])$/, (m,from,to)=> {\n pattern = [from,to];\n });\n return pattern;\n }\n }\n if (row[0] == \"STOP_GAINED\") {\n pattern = [];\n return;\n }\n let del_length = row[1].length - row[2].length;\n if (del_length) {\n pattern = +del_length;\n }\n return pattern;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1360,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":1940,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":1051,"value":"spatialVariantDensityByGene = _.map (make_spatial_clusters (genomeMap, (k)=>k, af_range[0], af_range[1], results.byVariant), (d)=> {\n d.density = d.count * 1000 / geneSize[d.coord] / results.samples;\n return d;\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":638,"value":"floatFormat = d3.format (\".2f\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":416,"value":"floatFmt = d3.format (\"2g\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":711,"value":"totalTreeLength = (tree)=> {\n let L = 0;\n tree.traverse_and_compute ( (n)=> {\n if (tree.branch_length (n)) {\n L += +tree.branch_length (n);\n }\n });\n return L;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":350,"value":"import {legend} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":904,"value":"obtainSourceData = async (p, src_url, is_tsv, is_json)=> {\n let sourceURL = src_url || null;\n if (!src_url) {\n p = p || new URLSearchParams(location.search);\n if (p.get(\"url\")) {\n sourceURL = p.get(\"url\");\n } \n }\n is_tsv = is_tsv || (p && p.get(\"format\") == \"tsv\");\n is_json = is_json || (p && p.get(\"format\") == \"json\")\n\n if (sourceURL.indexOf (\".gz\") == sourceURL.length - 3) {\n if (is_json) \n return JSON.parse (pako.inflate(await d3.buffer (sourceURL),{ to: 'string' }));\n if (is_tsv)\n return d3.tsvParse(pako.inflate(await d3.buffer (sourceURL),{ to: 'string' }), d3.autoType);\n return d3.csvParse(pako.inflate(await d3.buffer (sourceURL),{ to: 'string' }), d3.autoType);\n }\n \n let src;\n if (is_json) {\n src = await d3.json (sourceURL);\n } else {\n if (is_tsv) {\n src = await d3.tsv (sourceURL, d3.autoType);\n } else {\n src = await d3.csv (sourceURL, d3.autoType);\n }\n }\n return src;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1892,"value":"acknF = (d)=> {\n if (d) {\n return table (_.map (d[3], (d)=> [d.country, [d.name, d.homepage], d.institute, d.publication]),\n {\n columns: [\n {\n key: '1',\n name: 'Contributor',\n render: (val)=> `${val[1] ? \"\" + val[0] + \"\" : val[0]}`,\n },\n {\n key: '0',\n name: 'Country'\n },\n {\n key: '2',\n name: 'Institute'\n },\n {\n key: '3',\n name: 'Publication'\n }\n ]\n });\n }\n return md`None provided`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":833,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":1534,"value":"timeFmt = d3.timeFormat (\"%Y/%m/%d\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"d3 = require (\"d3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"_=require(\"lodash\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":432,"value":"vegalite = require (\"vega-embed\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":901,"value":"pako = require('https://bundle.run/pako@2.0.3')","pinned":false,"hidden":false,"mode":"ojs"},{"id":174,"value":"import {select, button, text, input, autoSelect, checkbox} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":127,"value":"import { table } from \"@gampleman/table\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1067,"value":"import {rangeSlider} from '@mootari/range-slider'","pinned":false,"hidden":false,"mode":"ojs"},{"id":1596,"value":"import {barRangeSlider as rs} from \"@spond/selector-with-confirmation\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1038,"value":"import {genomeMap, geneSize, gene_coordinates, map2key} from \"@spond/exploring-sars-cov-2-intrahost-variation-spatial\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1793,"value":"import {poissonSupport} from \"@spond/exploring-sars-cov-2-intrahost-variation-descriptive\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":587,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":598,"value":"html``","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W3a","stdlib":"1","titling":"auto"}