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Squidpy - Spatial Single Cell Analysis in Python

Squidpy logo

Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.

Squidpy title figure

Visit our documentation for installation, tutorials, examples and more.

Manuscript

Please see our manuscript Palla, Spitzer et al. (2022) in Nature Methods to learn more.

Squidpy's key applications

  • Build and analyze the neighborhood graph from spatial coordinates.
  • Compute spatial statistics for cell-types and genes.
  • Efficiently store, analyze and visualize large tissue images, leveraging skimage.
  • Interactively explore spatial data with napari-spatialdata.

Installation

Install Squidpy via PyPI by running:

pip install squidpy

or via Conda as:

conda install -c conda-forge squidpy

Contributing to Squidpy

We are happy about any contributions! Before you start, check out our contributing guide.

Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

About

Tutorials for Squidpy

squidpy.readthedocs.io/en/stable/

Resources

Readme
MIT license

Code of conduct

Code of conduct

Contributing

Contributing
Activity
Custom properties

Stars

35 stars

Watchers

1 watching

Forks

25 forks
Report repository

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Contributors

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PyPIDownloadsCINotebooks CIDocumentationCoverageDiscourseZulip
Squidpy - Spatial Single Cell Analysis in Python
Squidpy logo
Squidpy is a tool for the analysis and visualization of spatial molecular data.
It builds on top of scanpy and anndata, from which it inherits modularity and scalability.
It provides analysis tools that leverages the spatial coordinates of the data, as well as
tissue images if available.
Squidpy title figure
Visit our documentation for installation, tutorials, examples and more.
Manuscript
Please see our manuscript Palla, Spitzer et al. (2022) in Nature Methods to learn more.
Squidpy's key applications
  • Build and analyze the neighborhood graph from spatial coordinates.
  • Compute spatial statistics for cell-types and genes.
  • Efficiently store, analyze and visualize large tissue images, leveraging skimage.
  • Interactively explore spatial data with napari-spatialdata.
Installation
Install Squidpy via PyPI by running:
pip install squidpy

or via Conda as:
conda install -c conda-forge squidpy

Contributing to Squidpy
We are happy about any contributions! Before you start, check out our contributing guide.
Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS.
Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
About
Tutorials for Squidpy
squidpy.readthedocs.io/en/stable/
Resources
Readme
MIT license
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Contributing
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, 'i');
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(function(){
try {
var __m = "*";
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Squidpy - Spatial Single Cell Analysis in Python
Squidpy logo
Squidpy is a tool for the analysis and visualization of spatial molecular data.
It builds on top of scanpy and anndata, from which it inherits modularity and scalability.
It provides analysis tools that leverages the spatial coordinates of the data, as well as
tissue images if available.
Squidpy title figure
Visit our documentation for installation, tutorials, examples and more.
Manuscript
Please see our manuscript Palla, Spitzer et al. (2022) in Nature Methods to learn more.
Squidpy's key applications
  • Build and analyze the neighborhood graph from spatial coordinates.
  • Compute spatial statistics for cell-types and genes.
  • Efficiently store, analyze and visualize large tissue images, leveraging skimage.
  • Interactively explore spatial data with napari-spatialdata.
Installation
Install Squidpy via PyPI by running:
pip install squidpy

or via Conda as:
conda install -c conda-forge squidpy

Contributing to Squidpy
We are happy about any contributions! Before you start, check out our contributing guide.
Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS.
Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
About
Tutorials for Squidpy
squidpy.readthedocs.io/en/stable/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
35 stars
Watchers
1 watching
Forks
25 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PyPIDownloadsCINotebooks CIDocumentationCoverageDiscourseZulip
Squidpy - Spatial Single Cell Analysis in Python
Squidpy logo
Squidpy is a tool for the analysis and visualization of spatial molecular data.
It builds on top of scanpy and anndata, from which it inherits modularity and scalability.
It provides analysis tools that leverages the spatial coordinates of the data, as well as
tissue images if available.
Squidpy title figure
Visit our documentation for installation, tutorials, examples and more.
Manuscript
Please see our manuscript Palla, Spitzer et al. (2022) in Nature Methods to learn more.
Squidpy's key applications
  • Build and analyze the neighborhood graph from spatial coordinates.
  • Compute spatial statistics for cell-types and genes.
  • Efficiently store, analyze and visualize large tissue images, leveraging skimage.
  • Interactively explore spatial data with napari-spatialdata.
Installation
Install Squidpy via PyPI by running:
pip install squidpy

or via Conda as:
conda install -c conda-forge squidpy

Contributing to Squidpy
We are happy about any contributions! Before you start, check out our contributing guide.
Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS.
Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
About
Tutorials for Squidpy
squidpy.readthedocs.io/en/stable/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
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Stars
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Watchers
1 watching
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25 forks
Report repository
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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");
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})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
PyPIDownloadsCINotebooks CIDocumentationCoverageDiscourseZulip
Squidpy - Spatial Single Cell Analysis in Python
Squidpy logo
Squidpy is a tool for the analysis and visualization of spatial molecular data.
It builds on top of scanpy and anndata, from which it inherits modularity and scalability.
It provides analysis tools that leverages the spatial coordinates of the data, as well as
tissue images if available.
Squidpy title figure
Visit our documentation for installation, tutorials, examples and more.
Manuscript
Please see our manuscript Palla, Spitzer et al. (2022) in Nature Methods to learn more.
Squidpy's key applications
  • Build and analyze the neighborhood graph from spatial coordinates.
  • Compute spatial statistics for cell-types and genes.
  • Efficiently store, analyze and visualize large tissue images, leveraging skimage.
  • Interactively explore spatial data with napari-spatialdata.
Installation
Install Squidpy via PyPI by running:
pip install squidpy

or via Conda as:
conda install -c conda-forge squidpy

Contributing to Squidpy
We are happy about any contributions! Before you start, check out our contributing guide.
Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS.
Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
About
Tutorials for Squidpy
squidpy.readthedocs.io/en/stable/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
35 stars
Watchers
1 watching
Forks
25 forks
Report repository
Releases
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Contributors
Languages

, '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('^' + ".*" + '

Skip to content
BranchesTags
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PyPIDownloadsCINotebooks CIDocumentationCoverageDiscourseZulip
Squidpy - Spatial Single Cell Analysis in Python
Squidpy logo
Squidpy is a tool for the analysis and visualization of spatial molecular data.
It builds on top of scanpy and anndata, from which it inherits modularity and scalability.
It provides analysis tools that leverages the spatial coordinates of the data, as well as
tissue images if available.
Squidpy title figure
Visit our documentation for installation, tutorials, examples and more.
Manuscript
Please see our manuscript Palla, Spitzer et al. (2022) in Nature Methods to learn more.
Squidpy's key applications
  • Build and analyze the neighborhood graph from spatial coordinates.
  • Compute spatial statistics for cell-types and genes.
  • Efficiently store, analyze and visualize large tissue images, leveraging skimage.
  • Interactively explore spatial data with napari-spatialdata.
Installation
Install Squidpy via PyPI by running:
pip install squidpy

or via Conda as:
conda install -c conda-forge squidpy

Contributing to Squidpy
We are happy about any contributions! Before you start, check out our contributing guide.
Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS.
Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
About
Tutorials for Squidpy
squidpy.readthedocs.io/en/stable/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
35 stars
Watchers
1 watching
Forks
25 forks
Report repository
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Languages

, '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('^' + ".*" + '

Skip to content
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PyPIDownloadsCINotebooks CIDocumentationCoverageDiscourseZulip
Squidpy - Spatial Single Cell Analysis in Python
Squidpy logo
Squidpy is a tool for the analysis and visualization of spatial molecular data.
It builds on top of scanpy and anndata, from which it inherits modularity and scalability.
It provides analysis tools that leverages the spatial coordinates of the data, as well as
tissue images if available.
Squidpy title figure
Visit our documentation for installation, tutorials, examples and more.
Manuscript
Please see our manuscript Palla, Spitzer et al. (2022) in Nature Methods to learn more.
Squidpy's key applications
  • Build and analyze the neighborhood graph from spatial coordinates.
  • Compute spatial statistics for cell-types and genes.
  • Efficiently store, analyze and visualize large tissue images, leveraging skimage.
  • Interactively explore spatial data with napari-spatialdata.
Installation
Install Squidpy via PyPI by running:
pip install squidpy

or via Conda as:
conda install -c conda-forge squidpy

Contributing to Squidpy
We are happy about any contributions! Before you start, check out our contributing guide.
Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS.
Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
About
Tutorials for Squidpy
squidpy.readthedocs.io/en/stable/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
35 stars
Watchers
1 watching
Forks
25 forks
Report repository
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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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PyPIDownloadsCINotebooks CIDocumentationCoverageDiscourseZulip
Squidpy - Spatial Single Cell Analysis in Python
Squidpy logo
Squidpy is a tool for the analysis and visualization of spatial molecular data.
It builds on top of scanpy and anndata, from which it inherits modularity and scalability.
It provides analysis tools that leverages the spatial coordinates of the data, as well as
tissue images if available.
Squidpy title figure
Visit our documentation for installation, tutorials, examples and more.
Manuscript
Please see our manuscript Palla, Spitzer et al. (2022) in Nature Methods to learn more.
Squidpy's key applications
  • Build and analyze the neighborhood graph from spatial coordinates.
  • Compute spatial statistics for cell-types and genes.
  • Efficiently store, analyze and visualize large tissue images, leveraging skimage.
  • Interactively explore spatial data with napari-spatialdata.
Installation
Install Squidpy via PyPI by running:
pip install squidpy

or via Conda as:
conda install -c conda-forge squidpy

Contributing to Squidpy
We are happy about any contributions! Before you start, check out our contributing guide.
Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS.
Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
About
Tutorials for Squidpy
squidpy.readthedocs.io/en/stable/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
35 stars
Watchers
1 watching
Forks
25 forks
Report repository
Releases
Packages
Contributors
Languages