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 rising junior 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":672,"value":"html `

The following individuals contributed to this notebook:\n

Carolyn Bremer
Erika Nemeth, Notebook
Richard Moffitt, Ph.D., Notebook
Jonas Almeida, Ph.D., Notebook

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":683,"value":"html `

For a overview of our project I recommend reading through Erika Nemeth's notebook.\n

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":700,"value":"html `

To see what Erika and I did for each meeting of our project team I recommend reading through the rest of my notebook.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":713,"value":"md` **Overarching Project Motivation:** To utilize bioinformatics in order to catalogue the mutations that occur at different stages of cancer progression for the larger purposes of better understanding the biological manifestations of cancer and developing more precise therapies. We hope that this may be accomplished by making cancer genomic data more accessible to researchers and citizen scientists via web design. To this end, we will utilize JavaScript in handling of genomic data. (From Erika Nemeth's notebook)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":580,"value":"html`
Preparation for 5/3/19
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":582,"value":"md `- Try calling methods and data from Firebrowse\n- Moving forward: \n - Dealing with the lack of SSL\n - Alter following methods for BRCA gene instead\n - Can we call Firebrowse somewhere besides observable? Such as on chrome?`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":649,"value":"md`**Example:** http://firebrowse.org/iCoMut/?cohort=BLCA&order=ABCDEFGHIJKLMNOPQRST&expansion=11111111111111111111`","pinned":false,"hidden":false,"mode":"ojs"},{"id":661,"value":"md`**Below I played around with Firebrowse and methods from Jonas Almeida's notebook:** https://observablehq.com/@episphere/blca`","pinned":false,"hidden":false,"mode":"ojs"},{"id":614,"value":"myurl = 'http://firebrowse.org/api/v1/Samples/mRNASeq?format=json&gene=TP53&cohort=BLCA&protocol=RSEM&page=1&page_size=1000&sort_by=cohort'","pinned":false,"hidden":false,"mode":"ojs"},{"id":629,"value":"getURL = (await fetch('https://blca.herokuapp.com/?'+encodeURIComponent(myurl))).json() ","pinned":false,"hidden":false,"mode":"ojs"},{"id":617,"value":"plotNow([{\n y:getURL.mRNASeq.map(ex=>ex['expression_log2']),\n x:getURL.mRNASeq.map(ex=>ex['z-score']),\n ids:getURL.mRNASeq.map(ex=>ex['tcga_participant_barcode']),\n mode: 'markers',\n type: 'scatter',\n}],{\n title:'BLCA, FireBrowse mRNASeq expression data on TP53',\n yaxis:{\n title:'gene expression, log2',\n },\n xaxis:{\n title:'z-score',\n }\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":611,"value":"html`
Following imports and methods from Jonas Almeda
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":642,"value":"getURL.mRNASeq.map(ex=>ex['tcga_participant_barcode'])","pinned":false,"hidden":false,"mode":"ojs"},{"id":635,"value":"plotNow=async function(trace,layout){\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,layout)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":587,"value":"import {blca} from '@episphere/blca'","pinned":false,"hidden":false,"mode":"ojs"},{"id":515,"value":"html`
5/3/19 Continued (Preparation for 4/26/19)
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":567,"value":"md `**Goals:**`","pinned":false,"hidden":false,"mode":"ojs"},{"id":570,"value":"md `- Query gene expression for gender comparison`","pinned":false,"hidden":false,"mode":"ojs"},{"id":523,"value":"md `\n- Query each field/endpoint and show what returns\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":529,"value":"import {betterFetch} from \"@rmoffitt/webgen\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":534,"value":"flexibleData = async function(url,fields,from,size){\n let body = ({\n 'fields': fields,\n 'from': from,\n 'size': size\n })\n return(await betterFetch(url,body))\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":539,"value":"fieldData = flexibleData('https://api.gdc.cancer.gov/projects', \"disease_type\", 0, 100)","pinned":true,"hidden":false,"mode":"ojs"},{"id":544,"value":"fieldPlotter= async function(field){\n let dtt={}\n let y = fieldData.data.hits.map(x=>{\n if(!dtt[x.field]){\n dtt[x.field]=0\n }\n dtt[x.field]+=1\n \n })\n return dtt\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":553,"value":"fieldPlot = fieldPlotter('disease_type')","pinned":true,"hidden":false,"mode":"ojs"},{"id":542,"value":"fieldGraph= {\n let div = DOM.element('div')\n let trace={\n x:Object.keys(fieldPlot),\n y:Object.keys(fieldPlot).map(tp=>fieldPlot[tp]),\n type:'bar'\n }\n return plt.plot(div,[trace])\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":481,"value":"html`
Preparation for 4/19/19
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":483,"value":"md `**Goals:**\n- Research other APIs\n- Look into using a database / cloud data to upload data and enable easier access\n- Move male and female data chart onto an html page\n- Figure out how to import GDC API data onto an html page`","pinned":false,"hidden":false,"mode":"ojs"},{"id":488,"value":"html`\n
From Erika's Notebook: What is GTEx?
\n
A project which seeks to explore tissue-specific gene expression and regulation
\n
Provides public access to non-diseased tissue data (i.e., gene expression data, QTL [quantitative trait locus] data, histology images) in about 1,000 individuals
\n
The GTEx site
\n
Jonas found that the data could be explored through two APIs: One native to GTEx and another via Ensembl. Reference Jonas's notebook for more information
\n
\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":504,"value":"md `\n**Question:** Could we create a web app that is similar to GTEx's Multi-Gene query but with GDC's mutation data? (we would need to figure out a way to extract that data and make it easily accessible)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":494,"value":"html`
Using a Database
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":496,"value":"md `\n- Provides a database management system with querying and connectivity capabilities\n- MySQL server works in a client and server system: including a multiple-threaded SQL server that supports various APIs (figure out if we could incorporate GDC or maybe GTEx)\n- Database vs. Repository: \n - Repository: Database that stores the data associated with objects is stored as rows in tables; central common point of file storage of a related nature (database of databases)\n - Database: simply a place to store data; structured file/set of files that store and organize data\n- **Question**: How can we use this in relation to the GDC API? Upload mutation data from GDC to a database?? \n`","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 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":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":true,"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":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":55,"value":"printTARGET(projectData);","pinned":false,"hidden":false,"mode":"ojs"},{"id":328,"value":"html `
Miscellaneous
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":107,"value":"md`### *Notifications *\n\nhttps://api.gdc.cancer.gov/v0/notifications`","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}