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Scanpy – Single-Cell Analysis in Python

Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.

Discuss usage on the scverse Discourse. Read the documentation. If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.

scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse and want to support our mission, please consider making a donation to support our efforts.

Citation

If you use scanpy in your work, please cite the scanpy publication as follows:

SCANPY: large-scale single-cell gene expression data analysis

F. Alexander Wolf, Philipp Angerer, Fabian J. Theis

Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.

You can cite the scverse publication as follows:

The scverse project provides a computational ecosystem for single-cell omics data analysis

Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis

Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.

About

Single-Cell Analysis in Python. Scales to >1M cells.

scanpy.readthedocs.io

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Scanpy – Single-Cell Analysis in Python
Scanpy is a scalable toolkit for analyzing single-cell gene expression data
built jointly with anndata. It includes
preprocessing, visualization, clustering, trajectory inference and differential
expression testing. The Python-based implementation efficiently deals with
datasets of more than one million cells.
Discuss usage on the scverse Discourse. Read the documentation.
If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.
scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS.
If you like scverse and want to support our mission, please consider making a donation to support our efforts.
Citation
If you use scanpy in your work, please cite the scanpy publication as follows:
SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.
You can cite the scverse publication as follows:
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
About
Single-Cell Analysis in Python. Scales to >1M cells.
scanpy.readthedocs.io
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Scanpy – Single-Cell Analysis in Python
Scanpy is a scalable toolkit for analyzing single-cell gene expression data
built jointly with anndata. It includes
preprocessing, visualization, clustering, trajectory inference and differential
expression testing. The Python-based implementation efficiently deals with
datasets of more than one million cells.
Discuss usage on the scverse Discourse. Read the documentation.
If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.
scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS.
If you like scverse and want to support our mission, please consider making a donation to support our efforts.
Citation
If you use scanpy in your work, please cite the scanpy publication as follows:
SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.
You can cite the scverse publication as follows:
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
About
Single-Cell Analysis in Python. Scales to >1M cells.
scanpy.readthedocs.io
Resources
Readme
BSD-3-Clause license
Contributing
Contributing
Activity
Stars
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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StarsPyPIDownloadsCondaDocsBuild StatusDiscourse topicsChatPowered by NumFOCUS
Scanpy – Single-Cell Analysis in Python
Scanpy is a scalable toolkit for analyzing single-cell gene expression data
built jointly with anndata. It includes
preprocessing, visualization, clustering, trajectory inference and differential
expression testing. The Python-based implementation efficiently deals with
datasets of more than one million cells.
Discuss usage on the scverse Discourse. Read the documentation.
If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.
scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS.
If you like scverse and want to support our mission, please consider making a donation to support our efforts.
Citation
If you use scanpy in your work, please cite the scanpy publication as follows:
SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.
You can cite the scverse publication as follows:
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
About
Single-Cell Analysis in Python. Scales to >1M cells.
scanpy.readthedocs.io
Resources
Readme
BSD-3-Clause license
Contributing
Contributing
Activity
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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StarsPyPIDownloadsCondaDocsBuild StatusDiscourse topicsChatPowered by NumFOCUS
Scanpy – Single-Cell Analysis in Python
Scanpy is a scalable toolkit for analyzing single-cell gene expression data
built jointly with anndata. It includes
preprocessing, visualization, clustering, trajectory inference and differential
expression testing. The Python-based implementation efficiently deals with
datasets of more than one million cells.
Discuss usage on the scverse Discourse. Read the documentation.
If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.
scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS.
If you like scverse and want to support our mission, please consider making a donation to support our efforts.
Citation
If you use scanpy in your work, please cite the scanpy publication as follows:
SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.
You can cite the scverse publication as follows:
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
About
Single-Cell Analysis in Python. Scales to >1M cells.
scanpy.readthedocs.io
Resources
Readme
BSD-3-Clause license
Contributing
Contributing
Activity
Stars
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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StarsPyPIDownloadsCondaDocsBuild StatusDiscourse topicsChatPowered by NumFOCUS
Scanpy – Single-Cell Analysis in Python
Scanpy is a scalable toolkit for analyzing single-cell gene expression data
built jointly with anndata. It includes
preprocessing, visualization, clustering, trajectory inference and differential
expression testing. The Python-based implementation efficiently deals with
datasets of more than one million cells.
Discuss usage on the scverse Discourse. Read the documentation.
If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.
scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS.
If you like scverse and want to support our mission, please consider making a donation to support our efforts.
Citation
If you use scanpy in your work, please cite the scanpy publication as follows:
SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.
You can cite the scverse publication as follows:
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
About
Single-Cell Analysis in Python. Scales to >1M cells.
scanpy.readthedocs.io
Resources
Readme
BSD-3-Clause license
Contributing
Contributing
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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StarsPyPIDownloadsCondaDocsBuild StatusDiscourse topicsChatPowered by NumFOCUS
Scanpy – Single-Cell Analysis in Python
Scanpy is a scalable toolkit for analyzing single-cell gene expression data
built jointly with anndata. It includes
preprocessing, visualization, clustering, trajectory inference and differential
expression testing. The Python-based implementation efficiently deals with
datasets of more than one million cells.
Discuss usage on the scverse Discourse. Read the documentation.
If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.
scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS.
If you like scverse and want to support our mission, please consider making a donation to support our efforts.
Citation
If you use scanpy in your work, please cite the scanpy publication as follows:
SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.
You can cite the scverse publication as follows:
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
About
Single-Cell Analysis in Python. Scales to >1M cells.
scanpy.readthedocs.io
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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StarsPyPIDownloadsCondaDocsBuild StatusDiscourse topicsChatPowered by NumFOCUS
Scanpy – Single-Cell Analysis in Python
Scanpy is a scalable toolkit for analyzing single-cell gene expression data
built jointly with anndata. It includes
preprocessing, visualization, clustering, trajectory inference and differential
expression testing. The Python-based implementation efficiently deals with
datasets of more than one million cells.
Discuss usage on the scverse Discourse. Read the documentation.
If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.
scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS.
If you like scverse and want to support our mission, please consider making a donation to support our efforts.
Citation
If you use scanpy in your work, please cite the scanpy publication as follows:
SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.
You can cite the scverse publication as follows:
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
About
Single-Cell Analysis in Python. Scales to >1M cells.
scanpy.readthedocs.io
Resources
Readme
BSD-3-Clause license
Contributing
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Activity
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