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plotbetas function
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@lorenasandoval88
lorenasandoval88 committed Apr 11, 2024
1 parent 5c6605d commit c5b3f86
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Showing 3 changed files with 21 additions and 144 deletions.
3 changes: 0 additions & 3 deletions index.html
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Original file line number Diff line number Diff line change
Expand Up @@ -196,9 +196,6 @@ <h6 style="color: rgb(6, 137, 231);">Select an EFO id below:</h6>


</div>
<button id="plotbetasButton"></button>

<div id="plotbetas">plotbetas</div>

<!-- scripts----------------------------------------------->
<script src="tabs.js"></script>
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4 changes: 2 additions & 2 deletions sdk/main.js
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Original file line number Diff line number Diff line change
Expand Up @@ -66,7 +66,7 @@ functions.filterUsers = async function(type, users) {
}


functions.get23 = async function(usersData) {
functions.get23 = async function(usersData) { // todo: add the txts to local storage
let arr23Txts = []
// console.log(",usersData.map(x=> x.phenotypes[Type II Diabetes])",usersData.map(x=> x.phenotypes["Type II Diabetes"]))//.phenotypes["Type II Diabetes"]))
let urls = usersData.map( x => x["genotype.download_url"]).slice(128,150)
Expand Down Expand Up @@ -260,7 +260,7 @@ functions.getscoreFiles = async function(pgsIds) {
scores.push(cachedData)
} else if (cachedData == null) {
console.log(i, "No cached data found for ", `${pgsIds[i]}`)
await functions.timeout(200); // pgs has 100 queries per minute limit
await functions.timeout(500); // pgs has 100 queries per minute limit
let notCachedData =
await (fetch(url)).then(function (response) {
return response.json()
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158 changes: 19 additions & 139 deletions sdk/plots.js
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Original file line number Diff line number Diff line change
Expand Up @@ -8,8 +8,7 @@ localforage.config({
localforage.INDEXEDDB,
localforage.LOCALSTORAGE,
localforage.WEBSQL
],
name: 'localforage'
], name: 'localforage'
});


Expand Down Expand Up @@ -196,10 +195,9 @@ snpPhenoDiv.on('plotly_click', async function (data) {
await functions.timeout(3000)

if (phenoData == null) {
await functions.timeout(6000)

phenoData = await ( (await fetch(cors+url))).json()
await functions.timeout(6000)
await functions.timeout(3000)
singleUserAllPhenotypesTable.setItem(url, phenoData)
}
// console.log(`getting ids for ${phenoLabel}`,row.id)
Expand Down Expand Up @@ -275,10 +273,7 @@ var layout = {
width: 500,
autosize: false,
// title: `Counts of PGS entries across ${allTraitsDt.length} Categories`,
margin: {
b: 220
},

margin: {t:5, b: 200},
yaxis: {
title: {
text: 'Category Counts',
Expand Down Expand Up @@ -322,12 +317,12 @@ let topBarTraitsDiv = document.getElementById("topBarTraits")
let traitList = traitFiles.sort((a, b) => b.associated_pgs_ids.length - a.associated_pgs_ids.length)
var layout = {
autosize: false,
height: 700,
width: 8000,
// height: 700,
width: 8000,
// title: `Counts of PGS entries across ${traitList.length} Traits`,
margin: {
// t: 200,
b: 400
t: 10,
b: 250
},
yaxis: {
title: {
Expand Down Expand Up @@ -413,67 +408,13 @@ topBarCategoriesDiv.on('plotly_click', async function (data) {
}];
plotly.newPlot('secondBarCategories', data, layout)
functions.createButton("secondBarCategories","button1", `download ${pgsIds.length} pgs IDs`,pgsIds);
//
// betas button
functions.createButton2("betasBarCategoriesButton","button1_2", `plot betas`);

// plot betas
// save texts for small models (<500 variants)
let pgsIds500 = scoreFiles.filter( x => x.variants_number <500).map(x=>x.id)
let txts = await Promise.all(pgsIds500.map(async x => (await sdk.loadScoreHm(x))))

output["myPgsTxts"]=txts
console.log(" output:", output)


document.getElementById('button1_2').addEventListener('click', function(event) {
let traces = {}
txts.map( x => {
let chr = x.cols.indexOf("hm_chr")
let pos = x.cols.indexOf("hm_pos")
let weight = x.cols.indexOf("effect_weight")
let obj = {};
x.dt.map( e=> obj[e[chr]+"_"+e[pos]] = e[weight])
traces[x.id] = obj
})
// output.pgs[`plot ${category} 500 var`] = traces
// console.log( "output.pgs",output.pgs)

let plotData= Object.keys(traces).map( x =>{
let obj = {
"y": Object.values(traces[x]),
"x": Object.keys(traces[x]),
"type": 'bar',
"opacity": 0.65,
"name":x,
}
return obj
} )
// console.log( "plotData",plotData.map( x => x.y).flat())//.sort((a,b) => a.x - b.x))
let betas = plotData.map( x => x.y).flat()
var layout = {
"barmode": 'overlay',
title: `betas for ${pgsIds500.length} "${category}" entries with < 500 variants`,
height: 1000,
// width: (txts.length*170)/(0.2),
xaxis:{
title: {
standoff: 5,
text: "chromosome_position"},
},
margin: {l:5,b: 200 },
yaxis: {title: {
standoff: 10,
text: "beta"},
range: [betas.sort((a, b) => a - b)[0], betas.sort((a, b) => b - a)[0]]},
showlegend: true,
legend: {x: -0.09, y: 1}
}
plotly.newPlot('betasBarCategories', plotData,layout,{showSendToCloud: true});

})
// plot betas
plotBetas(category, scoreFiles, 500, "betasBarCategories", "button1_2")
})


// pie chart of traits -----------------------------------
topBarCategoriesDiv.on('plotly_click', async function (data) {
var spinner = document.getElementById("spinner2");
Expand Down Expand Up @@ -548,58 +489,7 @@ topBarCategoriesDiv.on('plotly_click', async function (data) {
functions.createButton2("betasthirdBarCategoriesButton","button1_3", `plot betas`);

// plot betas
// save texts for small models (<500 variants)
//let txts = []
let pgsIds500 = res.filter( x => x.variants_number <500).map(x=>x.id)
let txts = await Promise.all(pgsIds500.map(async x => (await sdk.loadScoreHm(x))))
//pgsIds500.map(async x => txts.push((await sdk.loadScoreHm(x))) )
//output.pgs[`txts ${trait} 500 var`] = txts
output["myPgsTxts"] = txts.slice(0,40)
document.getElementById('button1_3').addEventListener('click', function(event) {
let traces = {}
txts.map( x => {
let chr = x.cols.indexOf("hm_chr")
let pos = x.cols.indexOf("hm_pos")
let weight = x.cols.indexOf("effect_weight")
let obj = {};
x.dt.map( e=> obj[e[chr]+"_"+e[pos]] = e[weight])
traces[x.id] = obj
})
output.pgs[`plot ${trait} 500 var`] = traces
// console.log( "output.pgs",output.pgs)

let plotData= Object.keys(traces).map( x =>{
let obj = {
"y": Object.values(traces[x]),
"x": Object.keys(traces[x]),
"type": 'bar',
"opacity": 0.65,
"name":x,
}
return obj
} )
// console.log( "plotData",plotData.map( x => x.y).flat())//.sort((a,b) => a.x - b.x))
let betas = plotData.map( x => x.y).flat()
var layout = {
"barmode": 'overlay',
title: `betas for ${pgsIds500.length} "${trait}" entries with < 500 variants`,
height: 1000,
// width: (txts.length*170)/(0.2),
xaxis:{
title: {
standoff: 5,
text: "chromosome_position"},
},
margin: {l:5,b: 200 },
yaxis: {title: {
standoff: 10,
text: "beta"},
range: [betas.sort((a, b) => a - b)[0], betas.sort((a, b) => b - a)[0]]},
showlegend: true,
legend: {x: -0.09, y: 1.1}
}
plotly.newPlot('betasthirdBarCategories', plotData,layout,{showSendToCloud: true});
})
plotBetas(trait, res, 500, "betasthirdBarCategories", "button1_3")
})
})

Expand Down Expand Up @@ -646,17 +536,9 @@ topBarTraitsDiv.on('plotly_click', async function (data) {
functions.createButton("secondBarTraitsButton","button3",`download ${scoreFiles.length} pgs IDs`, scoreFiles.map(x => x.id));
functions.createButton2("betassecondBarTraitsButton","button3_2", `plot betas`);

// save texts for small models (<500 variants)
//let txts = []
let pgsIds500 = scoreFiles.filter( x => x.variants_number <500).map(x=>x.id)
let txts = await Promise.all(pgsIds500.map(async x => (await sdk.loadScoreHm(x))))

// pgsIds500.map(async x => txts.push((await sdk.loadScoreHm(x))) )
// output.pgs[`txts ${trait} 500 var`] = txts
output["myPgsTxts"] = txts.slice(0,40)

let scoreFiles2 = (await functions.getscoreFiles(pgsIds500)).sort((a, b) => a.variants_number - b.variants_number)
plotBetas(trait, scoreFiles2, 500, "betassecondBarTraits", "button3_2")

// plot betas
plotBetas(trait, scoreFiles, 500, "betassecondBarTraits", "button3_2")

})

Expand Down Expand Up @@ -779,18 +661,18 @@ const plotBetas = async function (category, scoreFiles, var_num ,div, button) {
// width: (txts.length*170)/(0.2),
xaxis: {
title: {
standoff: 5,
standoff: 30,
text: "chromosome_position"
},
},

margin: {l:5,b: 200 },
margin: {l: 130,b: 200 },
yaxis: {title: {
standoff: 95,
//standoff: 5,
text: "beta values"},
range: [betas.sort((a, b) => a - b)[0], betas.sort((a, b) => b - a)[0]]},
showlegend: true,
legend: {x: -0.09, y: 1}
legend: {x: -0.5, y: 1}
}
plotly.newPlot(div, plotData, layout, {
showSendToCloud: true
Expand All @@ -816,6 +698,4 @@ const plotBetas = async function (category, scoreFiles, var_num ,div, button) {

// },

export{output}


export{output}

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