30:T577,printPrim = function(projectData) { let div = DOM.element('div') // set up the main object div.innerHTML='

TARGET Project types, sorted by primary site ()

' //formatting the titles above let ol=DOM.element('ol') // set up the sub-object which will contain our data div.appendChild(ol) //added sub-object to the main object let caseCount=0 projectData.data.hits.forEach(function(prj,i){ // for each hit (project) if ((/TARGET/.test(prj.id))) { //if the object is data from TCGA let li = DOM.element('li') // build up the header "li" (list item) li.innerHTML=`${prj.id}: ${prj.name} (${prj.summary.case_count})` //formats all the blue headers caseCount=caseCount+prj.summary.case_count ol.appendChild(li) // append the header "li" to the larger object "ol" let ul = DOM.element('ul') // build up the bullets "ul" prj.primary_site.forEach(function(dtp){ // for each disease_type let li = DOM.element('li') li.style.fontSize='small' li.innerHTML=dtp ul.appendChild(li) // append one bullet "li" to the list of bullets "ul" }) li.appendChild(ul) // append the bullets "ul" to the header "li" } }) div.querySelector('#caseCountSpan').textContent=caseCount return div };31:T562,printTCGA = function(projectData) { let div = DOM.element('div') // set up the main object div.innerHTML='

TCGA Project types in GDC ()

' //formatting the titles above let ol=DOM.element('ol') // set up the sub-object which will contain our data div.appendChild(ol) //added sub-object to the main object let caseCount=0 projectData.data.hits.forEach(function(prj,i){ // for each hit (project) if ((/TCGA/.test(prj.id))) { //if the object is data from TCGA let li = DOM.element('li') // build up the header "li" (list item) li.innerHTML=`${prj.id}: ${prj.name} (${prj.summary.case_count})` //formats all the blue headers caseCount=caseCount+prj.summary.case_count ol.appendChild(li) // append the header "li" to the larger object "ol" let ul = DOM.element('ul') // build up the bullets "ul" prj.disease_type.forEach(function(dtp){ // for each disease_type let li = DOM.element('li') li.style.fontSize='small' li.innerHTML=dtp ul.appendChild(li) // append one bullet "li" to the list of bullets "ul" }) li.appendChild(ul) // append the bullets "ul" to the header "li" } }) div.querySelector('#caseCountSpan').textContent=caseCount return div };32:T568,printTARGET = function(projectData) { let div = DOM.element('div') // set up the main object div.innerHTML='

TARGET Project types in GDC ()

' //formatting the titles above let ol=DOM.element('ol') // set up the sub-object which will contain our data div.appendChild(ol) //added sub-object to the main object let caseCount=0 projectData.data.hits.forEach(function(prj,i){ // for each hit (project) if ((/TARGET/.test(prj.id))) { //if the object is data from TCGA let li = DOM.element('li') // build up the header "li" (list item) li.innerHTML=`${prj.id}: ${prj.name} (${prj.summary.case_count})` //formats all the blue headers caseCount=caseCount+prj.summary.case_count ol.appendChild(li) // append the header "li" to the larger object "ol" let ul = DOM.element('ul') // build up the bullets "ul" prj.disease_type.forEach(function(dtp){ // for each disease_type let li = DOM.element('li') li.style.fontSize='small' li.innerHTML=dtp ul.appendChild(li) // append one bullet "li" to the list of bullets "ul" }) li.appendChild(ul) // append the bullets "ul" to the header "li" } }) div.querySelector('#caseCountSpan').textContent=caseCount return div };33:[] 2e:{"title":"Web Genomics ","cells":[{"id":0,"value":"html`

Web Genomics

`\n\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":27,"value":"md`*Notebook for WebGenomics [web4bio.github.io/webgen](http://web4bio.github.io/webgen) \n(Vertically Integrated Project (VIP) at Stony Brook University)*`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":356,"value":"html `

About me: Hello! I am Carolyn Bremer, a sophomore Computer Science student at Stony Brook University. I am interested in gaining more experience with data analysis, JavaScript and other web technologies.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":126,"value":"md` **Overall Motivation:** To develop a means through which genetic mutations may be traced at different stages of cancer progression for the purpose of developing more precise therapeutic approaches. `\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":114,"value":"md` **Goal:** \n- Pull a specific subset of breast cancer data from the GDC (specifically the different types of mutations and their severity)\n- Create a web app that uses a small set of the GDC and implement the following:\n - Display the mutation data for VEP, SIFT, PolyPhen\n - Create another graph that merges the three into one (we can see if that shows a trend in the data)\n - Expand to a larger set of data once familiar with JS and GDC API`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":129,"value":"md` **Data:**\n- Pick a specific cancer or region and take a small subset of it\n- Work with the subset first in order to get familiar with Github and JS`","pinned":false,"hidden":false,"mode":"ojs"},{"id":443,"value":"html`

Preparation for 4/5/19

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":447,"value":"md `Goals:\n- Make chart comparing male and female data\n- Look into extracting mutation data from GDC or another API\n- Confirm it is female data/male data being extracted`","pinned":false,"hidden":false,"mode":"ojs"},{"id":453,"value":"plotly=require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":451,"value":"plotIt=async function(trace){\n if(typeof(plotly)==\"undefined\"){\n let plotly= await require(\"https://cdn.plot.ly/plotly-latest.min.js\")\n }\n let div = DOM.element('div')\n trace=trace||false\n return plotly.plot(div,trace)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":463,"value":"maleDiseaseType=(await fetch('https://api.gdc.cancer.gov/cases?from=0&size=20000&filters={\"op\":\"=\",\"content\":{\"field\":\"demographic.gender\",\"value\":[\"male\"]}}')).json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":465,"value":"malePlot={\n let dtt={}\n let y = maleDiseaseType.data.hits.map(x=>{\n //debugger\n if(!dtt[x.primary_site]){\n dtt[x.primary_site]=0\n }\n dtt[x.primary_site]+=1\n \n })\n return dtt\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":468,"value":"femaleDiseaseType=(await fetch('https://api.gdc.cancer.gov/cases?from=0&size=20000&filters={\"op\":\"=\",\"content\":{\"field\":\"demographic.gender\",\"value\":[\"female\"]}}')).json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":470,"value":"femaleDisPlot={\n let dtt={}\n let y = femaleDiseaseType.data.hits.map(x=>{\n if(!dtt[x.disease_type]){\n dtt[x.disease_type]=0\n }\n dtt[x.disease_type]+=1\n \n })\n return dtt\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":455,"value":"plotIt([{\n x:Object.keys(femaleDisPlot),\n y:Object.keys(femaleDisPlot).map(tp=>femaleDisPlot[tp]),\n type:'bar',\n name:'Female Data'\n },\n {\n x:Object.keys(malePlot),\n y:Object.keys(malePlot).map(tp=>malePlot[tp]),\n type:'bar',\n name:'Male Data'\n }])","pinned":false,"hidden":false,"mode":"ojs"},{"id":369,"value":"html`

Preparation for 3/29/19

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":371,"value":"md `Goals:\n- Extract female case data instead(100 cases)\n- Make chart where x-axis is the disease type`","pinned":false,"hidden":false,"mode":"ojs"},{"id":424,"value":"cancerData=(await fetch('https://api.gdc.cancer.gov/cases?from=0&size=250&filters={\"op\":\"=\",\"content\":{\"field\":\"demographic.gender\",\"value\":[\"female\"]}}')).json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":431,"value":"cancerPlot={\n let dtt={}\n let y = cancerData.data.hits.map(x=>{\n if(!dtt[x.disease_type]){\n dtt[x.disease_type]=0\n }\n dtt[x.disease_type]+=1\n \n })\n return dtt\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":429,"value":"cancerGraph= {\n let div = DOM.element('div')\n let trace={\n x:Object.keys(cancerPlot),\n y:Object.keys(cancerPlot).map(tp=>cancerPlot[tp]),\n type:'bar'\n }\n return plt.plot(div,[trace])\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":419,"value":"md `### Sort by Data Category Instead of Data Type`","pinned":false,"hidden":false,"mode":"ojs"},{"id":411,"value":"femalePlotAlt={\n let dtt={}\n let y = femaleData.data.hits.map(x=>{\n if(!dtt[x.data_category]){\n dtt[x.data_category]=0\n }\n dtt[x.data_category]+=1\n \n })\n return dtt\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":413,"value":"Object.keys(femalePlotAlt).map(tp=>femalePlotAlt[tp])","pinned":false,"hidden":false,"mode":"ojs"},{"id":415,"value":"femaleGraph2= {\n let div = DOM.element('div')\n let trace={\n x:Object.keys(femalePlotAlt),\n y:Object.keys(femalePlotAlt).map(tp=>femalePlotAlt[tp]),\n type:'bar'\n }\n return plt.plot(div,[trace])\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":274,"value":"html `

3/15/19 Class

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":278,"value":"md `**Playing Around with Other User Interface Libraries**`","pinned":false,"hidden":false,"mode":"ojs"},{"id":276,"value":"require('@oncojs/lolliplot')\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":227,"value":"html`

Preparation for 3/15/19

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":289,"value":"md `- **Pulling only female data from the GDC API and plotting it**\n- **Work on pulling specific data points from the GDC not just all the data from females**`","pinned":false,"hidden":false,"mode":"ojs"},{"id":230,"value":"femaleData=(await fetch('https://api.gdc.cancer.gov/files?from=0&size=250&filters={\"op\":\"=\",\"content\":{\"field\":\"cases.demographic.gender\",\"value\":[\"female\"]}}')).json()","pinned":true,"hidden":false,"mode":"ojs"},{"id":248,"value":"femalePlot={\n let dtt={}\n let y = femaleData.data.hits.map(x=>{\n if(!dtt[x.data_type]){\n dtt[x.data_type]=0\n }\n dtt[x.data_type]+=1\n \n })\n return dtt\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":250,"value":"Object.keys(femalePlot).map(tp=>femalePlot[tp])","pinned":false,"hidden":false,"mode":"ojs"},{"id":253,"value":"femaleGraph= {\n let div = DOM.element('div')\n let trace={\n x:Object.keys(femalePlot),\n y:Object.keys(femalePlot).map(tp=>femalePlot[tp]),\n type:'bar'\n }\n return plt.plot(div,[trace])\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":222,"value":"html `

3/8/19

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":302,"value":"md `- **Code below is for pulling only male data**`","pinned":false,"hidden":false,"mode":"ojs"},{"id":205,"value":"malesUrl='https://api.gdc.cancer.gov/files?from=0&size='+n","pinned":false,"hidden":false,"mode":"ojs"},{"id":207,"value":"n=300","pinned":false,"hidden":false,"mode":"ojs"},{"id":210,"value":"dt = (await fetch(malesUrl)).json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":213,"value":"dataPlot={\n let dtt={}\n let y = dt.data.hits.map(x=>{\n if(!dtt[x.data_type]){\n dtt[x.data_type]=0\n }\n dtt[x.data_type]+=1\n \n })\n return dtt\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":216,"value":"plt=require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":157,"value":"newProjectData=(await fetch('https://api.gdc.cancer.gov/files?fields=disease_type,primary_site,name,program.name,project_id,summary.case_count&from=0&size=1000&sort=disease_type:asc')).json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":218,"value":"Object.keys(dataPlot).map(tp=>dataPlot[tp])","pinned":false,"hidden":false,"mode":"ojs"},{"id":220,"value":"plot= {\n let div = DOM.element('div')\n let trace={\n x:Object.keys(dataPlot),\n y:Object.keys(dataPlot).map(tp=>dataPlot[tp]),\n type:'bar'\n }\n return plt.plot(div,[trace])\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":313,"value":"html `

2/15/19

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":315,"value":"md `**Below I changed Moffit's code in the following ways:**\n- **TCGA was changed to Target**\n- **Bullet points are now the primary site instead of disease type**\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":180,"value":"printPrim(projectData); ","pinned":false,"hidden":false,"mode":"ojs"},{"id":95,"value":"html`

The Section Below Contains Code from Richard Moffit and Jonas Almedia's Observable

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":35,"value":"md`***Functions Used Below***`","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"projectData=(await fetch('https://api.gdc.cancer.gov/projects?fields=disease_type,primary_site,name,program.name,project_id,summary.case_count&from=0&size=1000&sort=disease_type:asc')).json()\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":155,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":21,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":24,"value":"printTCGA(projectData);","pinned":false,"hidden":false,"mode":"ojs"},{"id":50,"value":"md`## List of TARGET`","pinned":false,"hidden":false,"mode":"ojs"},{"id":97,"value":"md`- **Replaced TCGA with TARGET**\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":52,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":55,"value":"printTARGET(projectData);","pinned":false,"hidden":false,"mode":"ojs"},{"id":328,"value":"html `

Miscellaneous

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":107,"value":"md`### *Notifications *\n\nhttps://api.gdc.cancer.gov/v0/notifications`","pinned":false,"hidden":false,"mode":"ojs"},{"id":482,"value":"md`\n# loading big text file \nwith pancreas somatic mutations\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":485,"value":"url=\"https://raw.githubusercontent.com/web4bio/webgen/master/TCGA.PAAD.mutect.fea333b5-78e0-43c8-bf76-4c78dd3fac92.DR-10.0.somatic.maf\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":496,"value":"getData = async function(url){\n let txt = (await fetch(url)).text()\n //debugger\n return txt\n\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":502,"value":"getData(url)","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}