2b:null 2c:["$","title",null,{"children":"Local (Pairwise) Rubisco Alignment | lametskas | Observable"}] 31:T727,angleChartMain = { const realData = vl.markLine() .data(dataForAngleBetweenRubiscosAndItsNeighbors) .transform( vl.groupby(['reg']) .density('angle') .bandwidth(5) .cumulative(false) .groupby(['reg','concentration', 'numRubInner', 'numRub', 'volume']), ) .encode( vl.x({ axis:{ grid: false, labelFontSize: 15, titleFontSize: 15, tickCount: 4, } }).fieldQ('value').title(['Angle between a reference Rubisco', 'and its nearest neighbors (deg)']), vl.y({ axis:{ grid: false, labelFontSize: 15, titleFontSize: 15 //tickCount: 5 } }).fieldQ('density'), vl.color().fieldQ('concentration').title([`Rubisco Concentration (µM)`]).scale({scheme: 'viridis', domain: [400, 900]}).sort('descending').legend({orient: 'bottom', titleLimit: 300, width: 400, titleFontSize: 15, labelFontSize: 15, tickCount: 5}), vl.tooltip([ { field: 'reg', title: 'reg' }, { field: 'concentration', title: 'Rubisco concentration (µM)', format: ".0f"}, { field: 'numRubInner', title: 'Inner Rubiscos'} ]) ) const randomData = vl.markLine({size: 5}) .data(randomAngles) .transform( vl.groupby(['reg']).density('angle').cumulative(false).groupby(['numRub']) ) .encode( vl.x({axis:{grid: false}}).fieldQ('value'), vl.y({axis:{grid: false}}).fieldQ('density'), // .scale({type: 'log'}), vl.color({legend: {title: 'hello'}}).value('darkred').title('random'), vl.tooltip().fieldN('numRub') ) return vl .layer(realData, randomData) .width(350) //750 .height(200) //400 .config({view: {stroke: "transparent"}}) .render({renderer: 'svg'}) }32:T45d,//plot concentration vs. Rubisco alignment probability. Note this is currently broken because inner rubisco concentration is incorrect (need to remove distance for Rubisco occupied space) vl.markCircle() .data(alignedVsCarbData) .transform( vl.filter(`datum.innerConcentration > 200`), vl.calculate(`datum.volume*1E18`).as('volMicro') ) .encode( vl.x({axis:{grid: false}}).fieldQ('innerConcentration').title(['Inner RuBisCO concentration (µM)']), vl.y({axis:{grid: false}}).fieldQ('events').title('Count of neighboring RuBisCO pairs aligned by >25 deg').scale({type: 'log'}), vl.color().fieldQ('concentration').title([`RuBisCO Concentration (µM)`]).scale({scheme: 'plasma'}).sort('descending').legend({orient: 'bottom', titleLimit: 300, width: 400}), vl.size().fieldQ('volMicro').title('Carboxysome Volume (µm³)').legend({orient: 'bottom', titleLimit: 300, width: 400}), vl.tooltip(['carbIndex', 'events', 'numRub'])//.fieldN('carbIndex') ) .width(700) .height(500) .config({view: {stroke: "transparent"}}) .render({renderer: 'svg'})33:T4f2,//data dump for above plot //choose carboxysomes of interest, find Rubiscos with xyz positions within 2 Rubisco diameters (i.e. just the nearest of neighbors). Filters here are included to look at all vs. just non-shell Rubiscos, and to consider only CBs with certain concentrations or numbers of Rubisco complexes. This then allows plotting of the angles bewteen these Rubisco complexes from the allAngles data. dataForAngleBetweenRubiscosAndItsNeighbors = allAngles .filter(d => d.distance < rubiscoDiameter * 2 && d.inner) //look just at inner Rubiscos //.filter(d => d.distance < rubiscoDiameter * 2) //look at all Rubiscos .map(d => { d.concentration = 1000*(d.numRub/d.volume)/avogradoNumber //d.innerConcentration = 1000*(d.numRubInner/d.volume)/avogradoNumber //look only at inner Rubisco concentration WARNING FUNCTION BROKEN - INNER RUBISCO CALCULATION NEEDS TO BE REDONE TO ACCOUNT FOR LOST VOLUME return d }) .filter(d => d.numRubInner > 30) //only plot carboxysomes with more than 30 Rubiscos off the shell (eliminate super-sparse set) //.filter(d => d.innerConcentration > 200) .map(c => { const d = JSON.parse(JSON.stringify(c)) delete d['indexI'] delete d['indexJ'] delete d['inner'] return d })34:T535,//calculate the pairwise distance and angle between each pair of Rubiscos within a carboxysome. This allows us to plot histograms of neighbor angles to look for non-random behavior over certain spatial distances. allAngles = { const results = [] let c = 0 for (const carbIndex of Array.from(carboxysomes)) { const vol = carbVolumes.find(vol => vol.carbIndex === carbIndex) const data = allData.filter(rub => rub.reg === carbIndex) const numRubInner = data.filter(rub => vol.tagsInside.indexOf(rub.tag) !== -1).length const numRub = data.length const vectors = data.map(item => computeVector(item)) for (let i = 0; i < numRub - 1; i++) { // const neighbors = findNeighbors(data, data[i], rubiscoDiameter * 2) const itemI = data[i] const isInnerI = vol.tagsInside.indexOf(itemI.tag) !== -1 for (let j = i + 1; j < numRub; j++) { const itemJ = data[j] const result = { reg: carbIndex, numRub, numRubInner, volume: vol.volume, inner: isInnerI && vol.tagsInside.indexOf(itemJ.tag) !== -1, indexI: i, indexJ: j, angle: calcDeltaAngle(vectors[i], vectors[j]), distance: calculateDistance(itemI, itemJ) } results.push(result) } } } return results }35:T4bf,//data dump for above plot //calculate the number of aligned Rubiscos (past a certain cutoff) vs. the CB parameters to look at concentration dependence alignedVsCarbData = { const results = [] const angleInterval = [0, 25] for (const carbIndex of Array.from(carboxysomes)) { const vol = carbVolumes.find(vol => vol.carbIndex === carbIndex) const events = allAngles .filter(angle => angle.reg === carbIndex) .filter(angle => angle.inner) .filter(angle => angle.distance < rubiscoDiameter * 2) .filter(angle => angle.angle < angleInterval[1]) if (events.length > 0) { const sample = events[0] const numRub = sample.numRub const numRubInner = sample.numRubInner const numRubOutter = numRub - numRubInner const volume = sample.volume const concentration = 1000*(numRub/volume)/avogradoNumber const innerConcentration = 1000*(numRubInner/volume)/avogradoNumber const obj = { carbIndex, numRub, numRubInner, numRubOutter, volume, concentration, innerConcentration, events: events.length } results.push(obj) } } return results }36:[] 2f:{"id":"12a2e79fbda69404","slug":null,"title":"Local (Pairwise) Rubisco Alignment","thumbnail":"5b816919f305baec43ebede2adb45312c2de638a92097b2b535ac4c209a7ef4d","access_level":"public","create_time":"$D2022-05-05T18:37:37.312Z","update_time":"$D2023-05-24T22:53:16.949Z","view_time":null,"first_public_time":"$D2023-05-22T17:38:57.156Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"23c25df75ad9e2b8","login":"lametskas","name":"","avatar_url":"https://avatars-next.observableusercontent.com/a20b09ebec8b2b068cfb2e793b5fc4f72ff178a8750f68663dff951311ccef71","tier":"starter_2024"},"version":118,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"041c7ee26ed50f05","login":"lametskas","name":"","avatar_url":"https://avatars-next.observableusercontent.com/a20b09ebec8b2b068cfb2e793b5fc4f72ff178a8750f68663dff951311ccef71","tier":null}],"members":[{"type":"individual","id":"041c7ee26ed50f05","login":"lametskas","name":"","avatar_url":"https://avatars-next.observableusercontent.com/a20b09ebec8b2b068cfb2e793b5fc4f72ff178a8750f68663dff951311ccef71","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":2,"collection":{"id":"9926aa94d1fc49f6","slug":"newrubiscoanalysis","title":"CleanedUpAnalysis","owner":{"id":"23c25df75ad9e2b8","login":"lametskas","name":""}},"type":"notebook","body":{"title":"Local (Pairwise) Rubisco Alignment","cells":[{"id":0,"value":"# Local (Pairwise) Rubisco Alignment","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":29,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":66,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"md`# Major Computations`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":22,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"//compute a random orientation line for the plot\nrandomAngles = {\n const results = []\n const N = Math.ceil(rubPerCarbAvg)\n const vectors = computeRandomVectorsMarsaglia72(N)\n \n for (let i = 0; i < N - 1; i++) {\n for (let j = i + 1; j < N; j++) {\n const obj = {\n reg: 'random',\n numRub: N,\n indexI: i,\n indexJ: j,\n angle: calcDeltaAngle(vectors[i], vectors[j])\n }\n results.push(obj)\n }\n }\n return results\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":68,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":108,"value":"//Make a set of random vectors, for use in randomness queries\ncomputeRandomVectorsMarsaglia72 = (N = 100) => {\n const results = []\n for (let i = 0; i < N; i++) {\n let init = 2\n let v1, v2\n while (init >= 1) {\n v1 = 2*(Math.random() - 0.5)\n v2 = 2*(Math.random() - 0.5)\n init = v1*v1 + v2*v2\n }\n const vec = math.matrix([\n 2*v1*Math.sqrt(1 - init),\n 2*v2*Math.sqrt(1 - init),\n 1 - 2*init\n ])\n const normed = math.dotDivide(vec, math.norm(vec))\n results.push(normed)\n }\n return results\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":40,"value":"md`# Helper Functions`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":88,"value":"//calculate the vector in 3D tomogram space for each Rubisco\ncomputeVector = (item) => {\n const initVec = [0,0,1]\n const zMatrix = zRotMatrix(item.tdrot)\n const xMatrix = xRotMatrix(item.tilt)\n const z2Matrix = zRotMatrix(item.narot)\n const tr1 = math.multiply(initVec, z2Matrix)\n const tr2 = math.multiply(tr1, xMatrix)\n const tr3 = math.multiply(tr2, zMatrix)\n return tr3 ///math.norm(tr3))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":90,"value":"xRotMatrix = (thetaInDeg) => {\n const theta = Math.PI * thetaInDeg / 180 // * 180 / Math.PI\n return math.matrix(\n [\n [1,0,0],\n [0, math.cos(theta), -math.sin(theta)],\n [0, math.sin(theta), math.cos(theta)],\n ]\n )\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":92,"value":"zRotMatrix = (thetaInDeg) => {\n const theta = Math.PI * thetaInDeg / 180 // thetaInDeg * 180 / Math.PI\n return math.matrix(\n [\n [math.cos(theta), -math.sin(theta), 0],\n [math.sin(theta), math.cos(theta), 0],\n [0,0,1]\n ]\n )\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":97,"value":"//standard formula for the angle between two vectors\ncalcDeltaAngle = (vec1, vec2) => {\n return 180 * math.acos(math.abs(math.dot(vec1, vec2)/(math.norm(vec1) * math.norm(vec2)))) / Math.PI\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"rubPerCarbAvg = {\n let rubPerCarbAvg = 0\n for (const carbIndex of Array.from(carboxysomes)) {\n rubPerCarbAvg += allData.filter(rub => rub.reg === carbIndex).length\n }\n return rubPerCarbAvg/carboxysomes.size\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":102,"value":"calculateDistance = (source, target) => {\n const sub = math.subtract([source.x, source.y, source.z], [target.x, target.y, target.z])\n return math.norm(sub)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":112,"value":"findNeighbors = (dataset, target, radius) => dataset.filter(item => calculateDistance(item, target) < ( radius || 1000000) && target.tag !== item.tag)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"md`# Imports`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":8,"value":"import { carboxysomes, carbVolumes, allData, avogradoNumber, rubiscoDiameter } from 'af0568b05533fb86'\n// This refers to the NewBaseAnalysis page, importing base calculations","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"math = require(\"mathjs\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W36","stdlib":"1","titling":"auto"}} 30:"$2f:body"