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Procedure1.html
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<li><a href="#classification-evaluation" id="toc-classification-evaluation" class="nav-link" data-scroll-target="#classification-evaluation"><span class="header-section-number">2.4</span> Classification Evaluation</a></li>
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<h1 class="title"><span class="chapter-number">2</span> <span class="chapter-title">Comparing cross-validated results</span></h1>
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<section id="introduction" class="level2" data-number="2.1">
<h2 data-number="2.1" class="anchored" data-anchor-id="introduction"><span class="header-section-number">2.1</span> Introduction</h2>
<p>Procedure 1 aims to compare the sample accuracy of breast cancer subtype classification using bulk gene expression data and histologically predicted gene expression data. Sample accuracy is defined as the proportion of correctly predicted classifications over multiple repeats. For example, if 70 out of 100 repeats correctly classify an individual, their sample accuracy is 0.70.</p>
<p>This analysis involves 54 oestrogen receptor-positive (ER+) and progesterone receptor-positive (PR+) breast cancer patients, with each assay containing expression values for 268 genes. The classification outcomes are ‘Subtype 1’ and ‘Subtype 2’, found by unsupervised machine learning. Subtype 1 corresponds to patients with higher expression of LPL, CAVIN2, and TIMP4 in macrophage cells, and ADIPOQ in stromal cells, associated with better survival. Subtype 2 is the opposite, associated with poorer survival. More details on the subtypes can be found at https://www.biorxiv.org/content/10.1101/2024.07.02.601790v1.full.</p>
</section>
<section id="set-up-the-environment-and-data-objects" class="level2" data-number="2.2">
<h2 data-number="2.2" class="anchored" data-anchor-id="set-up-the-environment-and-data-objects"><span class="header-section-number">2.2</span> Set up the environment and data objects</h2>
<p><strong>1. Load the R packages into the R environment</strong></p>
<p><span style="color: grey;">Timing ~ 6.5s</span></p>
<div class="cell">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ClassifyR)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p><code>ClassifyR</code> is used to perform all the demonstrated analyses.</p>
<p><strong>2. Import preprocessed datasets for analysis</strong></p>
<p><span style="color: grey;">Timing ~ 0.04s</span></p>
<div class="cell">
<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>ghist_mae <span class="ot"><-</span> <span class="fu">readRDS</span>(<span class="st">"data/procedure1/ghist_multiassayexperiment.rds"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>This command reads in a MultiAssayExperiment with two assays. The first is bulk gene expression data for 54 breast cancer individuals and the second is bulk gene expression as predicted from histological images of the same individuals. They are respectively named bulk_gene_expression and histologically_predicted_gene_expression.</p>
</section>
<section id="cross-validated-classification" class="level2" data-number="2.3">
<h2 data-number="2.3" class="anchored" data-anchor-id="cross-validated-classification"><span class="header-section-number">2.3</span> Cross-validated Classification</h2>
<p><strong>3. Classifying patients into subtype outcomes</strong></p>
<p><span style="color: grey;">Timing ~ 45.0s</span></p>
<div class="cell">
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="fu">set.seed</span>(<span class="dv">1</span>)</span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>classifyr_result <span class="ot"><-</span> <span class="fu">crossValidate</span>(ghist_mae, <span class="at">outcome =</span> <span class="st">"subtype"</span>, <span class="at">nFolds =</span> <span class="dv">5</span>, <span class="at">nRepeats =</span> <span class="dv">100</span>, <span class="at">nCores =</span> <span class="dv">5</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>The <code>set.seed(1)</code> command ensures that any subsequent operations involving randomness yield consistent results across runs.</p>
<p>The next command uses the <code>crossValidate</code> function to perform 5-fold cross-validation with the automatically selected RandomForest classifier on both datasets. This process is repeated 100 times and utilizes 5 CPU cores for parallel processing to speed up classification. The type of classifier, number of folds, repeats and cores used can be adjusted as wished for different analyses. The outcome here is “subtype”, a column from <code>colData(ghist_mae)</code> containing the two breast cancer subtypes to be predicted.<br>
</p>
</section>
<section id="classification-evaluation" class="level2" data-number="2.4">
<h2 data-number="2.4" class="anchored" data-anchor-id="classification-evaluation"><span class="header-section-number">2.4</span> Classification Evaluation</h2>
<p><strong>4. Visualising the classification performance</strong></p>
<p><span style="color: grey;">Timing ~ 1.75s</span></p>
<div class="cell">
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="fu">performancePlot</span>(classifyr_result)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="Procedure1_files/figure-html/unnamed-chunk-4-1.png" class="img-fluid figure-img" width="672"></p>
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<p><code>performancePlot</code> outputs a side-by-side boxplot of the balanced accuracies for each dataset.<br>
Both methods perform comparably in terms of median balanced accuracy and also demonstrate similar distributions of performance as seen from the comparable interquartile range and range. There does not appear to be much difference in the classification performance of both assays.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="fu">samplesMetricMap</span>(classifyr_result)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
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<p><img src="Procedure1_files/figure-html/unnamed-chunk-5-1.png" class="img-fluid figure-img" width="672"></p>
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<div class="cell-output cell-output-stdout">
<pre><code>TableGrob (2 x 1) "arrange": 2 grobs
z cells name grob
1 1 (2-2,1-1) arrange gtable[layout]
2 2 (1-1,1-1) arrange text[GRID.text.274]</code></pre>
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<p><code>samplesMetricMap</code> outputs a heatmap showing the classification accuracy for each of 100 repeats in each sample. A greater proportion of samples show high sample accuracies (0.8,1] when classified by the expression data as opposed to the histological data.</p>
</section>
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button.setAttribute("data-bs-title", "Copied!");
tooltip = new bootstrap.Tooltip(button,
{ trigger: "manual",
customClass: "code-copy-button-tooltip",
offset: [0, -8]});
tooltip.show();
}
setTimeout(function() {
if (tooltip) {
tooltip.hide();
button.removeAttribute("data-bs-title");
button.removeAttribute("data-bs-toggle");
button.removeAttribute("data-bs-placement");
}
button.setAttribute("title", currentTitle);
button.classList.remove('code-copy-button-checked');
}, 1000);
// clear code selection
e.clearSelection();
});
var localhostRegex = new RegExp(/^(?:http|https):\/\/localhost\:?[0-9]*\//);
var mailtoRegex = new RegExp(/^mailto:/);
var filterRegex = new RegExp('/' + window.location.host + '/');
var isInternal = (href) => {
return filterRegex.test(href) || localhostRegex.test(href) || mailtoRegex.test(href);
}
// Inspect non-navigation links and adorn them if external
var links = window.document.querySelectorAll('a[href]:not(.nav-link):not(.navbar-brand):not(.toc-action):not(.sidebar-link):not(.sidebar-item-toggle):not(.pagination-link):not(.no-external):not([aria-hidden]):not(.dropdown-item):not(.quarto-navigation-tool)');
for (var i=0; i<links.length; i++) {
const link = links[i];
if (!isInternal(link.href)) {
// undo the damage that might have been done by quarto-nav.js in the case of
// links that we want to consider external
if (link.dataset.originalHref !== undefined) {
link.href = link.dataset.originalHref;
}
}
}
function tippyHover(el, contentFn, onTriggerFn, onUntriggerFn) {
const config = {
allowHTML: true,
maxWidth: 500,
delay: 100,
arrow: false,
appendTo: function(el) {
return el.parentElement;
},
interactive: true,
interactiveBorder: 10,
theme: 'quarto',
placement: 'bottom-start',
};
if (contentFn) {
config.content = contentFn;
}
if (onTriggerFn) {
config.onTrigger = onTriggerFn;
}
if (onUntriggerFn) {
config.onUntrigger = onUntriggerFn;
}
window.tippy(el, config);
}
const noterefs = window.document.querySelectorAll('a[role="doc-noteref"]');
for (var i=0; i<noterefs.length; i++) {
const ref = noterefs[i];
tippyHover(ref, function() {
// use id or data attribute instead here
let href = ref.getAttribute('data-footnote-href') || ref.getAttribute('href');
try { href = new URL(href).hash; } catch {}
const id = href.replace(/^#\/?/, "");
const note = window.document.getElementById(id);
if (note) {
return note.innerHTML;
} else {
return "";
}
});
}
const xrefs = window.document.querySelectorAll('a.quarto-xref');
const processXRef = (id, note) => {
// Strip column container classes
const stripColumnClz = (el) => {
el.classList.remove("page-full", "page-columns");
if (el.children) {
for (const child of el.children) {
stripColumnClz(child);
}
}
}
stripColumnClz(note)
if (id === null || id.startsWith('sec-')) {
// Special case sections, only their first couple elements
const container = document.createElement("div");
if (note.children && note.children.length > 2) {
container.appendChild(note.children[0].cloneNode(true));
for (let i = 1; i < note.children.length; i++) {
const child = note.children[i];
if (child.tagName === "P" && child.innerText === "") {
continue;
} else {
container.appendChild(child.cloneNode(true));
break;
}
}
if (window.Quarto?.typesetMath) {
window.Quarto.typesetMath(container);
}
return container.innerHTML
} else {
if (window.Quarto?.typesetMath) {
window.Quarto.typesetMath(note);
}
return note.innerHTML;
}
} else {
// Remove any anchor links if they are present
const anchorLink = note.querySelector('a.anchorjs-link');
if (anchorLink) {
anchorLink.remove();
}
if (window.Quarto?.typesetMath) {
window.Quarto.typesetMath(note);
}
// TODO in 1.5, we should make sure this works without a callout special case
if (note.classList.contains("callout")) {
return note.outerHTML;
} else {
return note.innerHTML;
}
}
}
for (var i=0; i<xrefs.length; i++) {
const xref = xrefs[i];
tippyHover(xref, undefined, function(instance) {
instance.disable();
let url = xref.getAttribute('href');
let hash = undefined;
if (url.startsWith('#')) {
hash = url;
} else {
try { hash = new URL(url).hash; } catch {}
}
if (hash) {
const id = hash.replace(/^#\/?/, "");
const note = window.document.getElementById(id);
if (note !== null) {
try {
const html = processXRef(id, note.cloneNode(true));
instance.setContent(html);
} finally {
instance.enable();
instance.show();
}
} else {
// See if we can fetch this
fetch(url.split('#')[0])
.then(res => res.text())
.then(html => {
const parser = new DOMParser();
const htmlDoc = parser.parseFromString(html, "text/html");
const note = htmlDoc.getElementById(id);
if (note !== null) {
const html = processXRef(id, note);
instance.setContent(html);
}
}).finally(() => {
instance.enable();
instance.show();
});
}
} else {
// See if we can fetch a full url (with no hash to target)
// This is a special case and we should probably do some content thinning / targeting
fetch(url)
.then(res => res.text())
.then(html => {
const parser = new DOMParser();
const htmlDoc = parser.parseFromString(html, "text/html");
const note = htmlDoc.querySelector('main.content');
if (note !== null) {
// This should only happen for chapter cross references
// (since there is no id in the URL)
// remove the first header
if (note.children.length > 0 && note.children[0].tagName === "HEADER") {
note.children[0].remove();
}
const html = processXRef(null, note);
instance.setContent(html);
}
}).finally(() => {
instance.enable();
instance.show();
});
}
}, function(instance) {
});
}
let selectedAnnoteEl;
const selectorForAnnotation = ( cell, annotation) => {
let cellAttr = 'data-code-cell="' + cell + '"';
let lineAttr = 'data-code-annotation="' + annotation + '"';
const selector = 'span[' + cellAttr + '][' + lineAttr + ']';
return selector;
}
const selectCodeLines = (annoteEl) => {
const doc = window.document;
const targetCell = annoteEl.getAttribute("data-target-cell");
const targetAnnotation = annoteEl.getAttribute("data-target-annotation");
const annoteSpan = window.document.querySelector(selectorForAnnotation(targetCell, targetAnnotation));
const lines = annoteSpan.getAttribute("data-code-lines").split(",");
const lineIds = lines.map((line) => {
return targetCell + "-" + line;
})
let top = null;
let height = null;
let parent = null;
if (lineIds.length > 0) {
//compute the position of the single el (top and bottom and make a div)
const el = window.document.getElementById(lineIds[0]);
top = el.offsetTop;
height = el.offsetHeight;
parent = el.parentElement.parentElement;
if (lineIds.length > 1) {
const lastEl = window.document.getElementById(lineIds[lineIds.length - 1]);
const bottom = lastEl.offsetTop + lastEl.offsetHeight;
height = bottom - top;
}
if (top !== null && height !== null && parent !== null) {
// cook up a div (if necessary) and position it
let div = window.document.getElementById("code-annotation-line-highlight");
if (div === null) {
div = window.document.createElement("div");
div.setAttribute("id", "code-annotation-line-highlight");
div.style.position = 'absolute';
parent.appendChild(div);
}
div.style.top = top - 2 + "px";
div.style.height = height + 4 + "px";
div.style.left = 0;
let gutterDiv = window.document.getElementById("code-annotation-line-highlight-gutter");
if (gutterDiv === null) {
gutterDiv = window.document.createElement("div");
gutterDiv.setAttribute("id", "code-annotation-line-highlight-gutter");
gutterDiv.style.position = 'absolute';
const codeCell = window.document.getElementById(targetCell);
const gutter = codeCell.querySelector('.code-annotation-gutter');
gutter.appendChild(gutterDiv);
}
gutterDiv.style.top = top - 2 + "px";
gutterDiv.style.height = height + 4 + "px";
}
selectedAnnoteEl = annoteEl;
}
};
const unselectCodeLines = () => {
const elementsIds = ["code-annotation-line-highlight", "code-annotation-line-highlight-gutter"];
elementsIds.forEach((elId) => {
const div = window.document.getElementById(elId);
if (div) {
div.remove();
}
});
selectedAnnoteEl = undefined;
};
// Handle positioning of the toggle
window.addEventListener(
"resize",
throttle(() => {
elRect = undefined;
if (selectedAnnoteEl) {
selectCodeLines(selectedAnnoteEl);
}
}, 10)
);
function throttle(fn, ms) {
let throttle = false;
let timer;
return (...args) => {
if(!throttle) { // first call gets through
fn.apply(this, args);
throttle = true;
} else { // all the others get throttled
if(timer) clearTimeout(timer); // cancel #2
timer = setTimeout(() => {
fn.apply(this, args);
timer = throttle = false;
}, ms);
}
};
}
// Attach click handler to the DT
const annoteDls = window.document.querySelectorAll('dt[data-target-cell]');
for (const annoteDlNode of annoteDls) {
annoteDlNode.addEventListener('click', (event) => {
const clickedEl = event.target;
if (clickedEl !== selectedAnnoteEl) {
unselectCodeLines();
const activeEl = window.document.querySelector('dt[data-target-cell].code-annotation-active');
if (activeEl) {
activeEl.classList.remove('code-annotation-active');
}
selectCodeLines(clickedEl);
clickedEl.classList.add('code-annotation-active');
} else {
// Unselect the line
unselectCodeLines();
clickedEl.classList.remove('code-annotation-active');
}
});
}
const findCites = (el) => {
const parentEl = el.parentElement;
if (parentEl) {
const cites = parentEl.dataset.cites;
if (cites) {
return {
el,
cites: cites.split(' ')
};
} else {
return findCites(el.parentElement)
}
} else {
return undefined;
}
};
var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');
for (var i=0; i<bibliorefs.length; i++) {
const ref = bibliorefs[i];
const citeInfo = findCites(ref);
if (citeInfo) {
tippyHover(citeInfo.el, function() {
var popup = window.document.createElement('div');
citeInfo.cites.forEach(function(cite) {
var citeDiv = window.document.createElement('div');
citeDiv.classList.add('hanging-indent');
citeDiv.classList.add('csl-entry');
var biblioDiv = window.document.getElementById('ref-' + cite);
if (biblioDiv) {
citeDiv.innerHTML = biblioDiv.innerHTML;
}
popup.appendChild(citeDiv);
});
return popup.innerHTML;
});
}
}
});
</script>
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<div class="nav-page nav-page-previous">
<a href="./index.html" class="pagination-link" aria-label="Overview">
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</a>
</div>
<div class="nav-page nav-page-next">
<a href="./Procedure3.html" class="pagination-link" aria-label="Multi-Platform Precision Pathway">
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</div>
</nav>
</div> <!-- /content -->
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