31:[{"id":"5ee88de74750914f36ddf59d2b4d877edbec051fa794653304c75fc25facfa7cba397b1b7b6fc2cdb8812c23807b658f1463b9ba9286054ea39de0e237029ad1","href":"https://static.observableusercontent.com/files/5ee88de74750914f36ddf59d2b4d877edbec051fa794653304c75fc25facfa7cba397b1b7b6fc2cdb8812c23807b658f1463b9ba9286054ea39de0e237029ad1","name":"fel-2023@3.csv","type":"text/csv","lastModified":1691970692373.482,"size":587845}] 2f:{"title":"SARS-CoV-2 global genomic selection (2019-Aug 2023)","cells":[{"id":4,"value":"# SARS-CoV-2 global genomic selection (2019-Aug 2023)\n\nThis is a gene-by-gene analysis of a global (all locations, all times, up to the first week of August 2023) subsample with ~75,000 SARS-CoV-2 genomes to quantify site-by-site selective pressure. The FEL (2.5) method in HyPhy 2.5.53 was run using **internal** tree branches as the test set.
The subsample was generated by [Steven Weaver](https://observablehq.com/@stevenweaver) from GISAID data","pinned":false,"hidden":false,"mode":"md"},{"id":20,"value":"viewof p_value = Inputs.text({'value' : 0.05, 'label' : 'p-value cutoff', 'submit': true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"viewof search = Inputs.search(table_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":41,"value":"viewof table_filter = Inputs.checkbox([\"Diversifying\", \"Purifying\", \"Neutral\",\"Invariable\"], {value: [\"Diversifying\", \"Purifying\", \"Neutral\", \"Invariable\"], label: html`Show`, format: x => html`${x}`})","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"Inputs.table(search, {\n rows: 15,\n sort: \"Location\",\n format: {\n Class : (d)=>html`${d}`,\n \"p-value\" : (d)=>d\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":81,"value":"Plot.dot(search, {x: \"Location\", y: \"p-value\", \"fill\" : \"Class\"}).plot({width:800,color: {legend: true}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":84,"value":"table_data = _.filter (data, (x)=>table_filter.indexOf (x.Class)>=0)","pinned":false,"hidden":false,"mode":"ojs"},{"id":35,"value":"data = {\n return _.map (raw_data, (d)=> {\n return {\n 'Location' : d.genome_coord,\n 'Codon' : d.gene_orf + \"/\" + d.codon,\n 'Sequences' : d.seqs,\n 'Tree Length' : d.T,\n 'α' : d.alpha,\n 'β' : d.beta,\n 'p-value' : d.p_value,\n 'Class' : d.alpha + d.beta > 0 ? (d.p_value <= p_value ? (d.alpha < d.beta ? \"Diversifying\" : \"Purifying\") : \"Neutral\") : \"Invariable\"\n }\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":43,"value":"table_colors = ({\n 'Diversifying' : '#e3243b',\n 'Neutral' : '#444',\n 'Purifying' : 'green',\n 'Invariable' : '#CCC'\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"raw_data = await FileAttachment(\"fel-2023@3.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W31","stdlib":"1","titling":"auto"}