Python package for systematic assessment of clustering results stability on single-cell data.
Project description
# ClustAssessPy
[![Downloads](https://static.pepy.tech/badge/ClustAssessPy)](https://pepy.tech/project/ClustAssessPy) [![Downloads](https://static.pepy.tech/badge/ClustAssessPy/week)](https://pepy.tech/project/ClustAssessPy)
ClustAssessPy offers a data-driven approach for optimizing parameter values across all stages of graph-based community detection clustering in single-cell datasets. This Python package is a lighter adaptation of ClustAssess (R) [1], incorporating its main functions and can be used by the Scanpy community to guide robust clustering through data-driven selection in all community detection clustering steps:
Dimensionality Reduction: Selection of the base embedding (UMAP vs PCA) and the number and type of features (e.g., highly-variable vs most abundant).
Graph Type: Choice of graph type for the adjacency matrix (nearest neighbors vs shared nearest neighbors) and the number of neighbors.
Clustering: Identification of the most stable algorithm (Leiden or Louvain) and the appropriate resolution value.
## Installation
ClustAssessPy requires Python 3.7 or newer.
### Dependencies
numpy
pandas
scanpy
umap-learn
seaborn
matplotlib
scipy
networkx
plotnine
pynndescent
leidenalg
louvain
igraph
### User Installation
We recommend that you download ClustAssessPy on a virtual environment (venv or Conda).
`sh pip install ClustAssessPy `
## Getting Started
Documentation for the main functions is available [here](https://core-bioinformatics.github.io/ClustAssessPy/ClustAssessPy.html). For a detailed tutorial, click [here](https://github.com/Core-Bioinformatics/ClustAssessPy/blob/main/Examples/tutorial_cuomo.ipynb).
## References
[1] Shahsavari, A., Munteanu, A., & Mohorianu, I. (2022). ClustAssess: Tools for Assessing the Robustness of Single-Cell Clustering. https://doi.org/10.1101/2022.01.31.478592
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SHA256 | c10a98cd7fac34da1e83f47da7b7f49ba77b970a8e475a21e3801048380acd09 |
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MD5 | 09a16d2f3d37f060e03a66a6beeecfed |
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BLAKE2b-256 | 41686bc2190998df854678c576e17e05dbb00118a59423128095948e3e7caa3f |
Hashes for ClustAssessPy-1.0.1-cp39-cp39-win_amd64.whl
Algorithm | Hash digest | |
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SHA256 | 7bb67be55fd3dde39a0886853b7a2e4303391275dee4cde487cd88ad0799351f |
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MD5 | 42d42190fa39c57126d01fbdd04387fd |
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BLAKE2b-256 | ae59fe5866158fa139e19cf8c44bea56ea423c6dd0d1512be77c09d8332cd702 |
Hashes for ClustAssessPy-1.0.1-cp39-cp39-win32.whl
Algorithm | Hash digest | |
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SHA256 | 8fd52a857ebdb6ce5b525a092fdcda4bdb3b761c95e6c5a0b5f497cc6de231c2 |
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MD5 | dde7ed6411ba5d1fe6830cb7be93fbe4 |
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BLAKE2b-256 | f670354c782454c01c7f4fda3658d393b0110ba35a276e4a0d4d5bcbaac31e89 |
Hashes for ClustAssessPy-1.0.1-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 65e59004d7484b1fe6852aa706eab412e9acd573d7bbe674cf633e5a74c4f42c |
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MD5 | b53970b2911e26ab035f6a6e2b803b24 |
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BLAKE2b-256 | f0fc5b8200a2026dd18cc3b9fc947cac92fc47e410ec9dee88cd80fcc6221cdb |
Hashes for ClustAssessPy-1.0.1-cp39-cp39-musllinux_1_2_i686.whl
Algorithm | Hash digest | |
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SHA256 | 3ca74a5d16caec36970aff8606dfa83dfc32a9c2ed79abfb305399788901cace |
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MD5 | b736ffa30f7fc720002583b808eb3296 |
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BLAKE2b-256 | ca0dc22ac22a6473d7dbcf42a0511767936682104cefaebed43e246647d36581 |
Hashes for ClustAssessPy-1.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 2567cf069e5b576d096027b7a98ed799a40c396792c619cdc947b6f6df841521 |
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MD5 | f33712e26a6c225f3c7d1e6d2dce9c96 |
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BLAKE2b-256 | 557c4488026a17b9b7576849854733aba5d1caa6788bd7cf5eaf5be9d184bb07 |
Hashes for ClustAssessPy-1.0.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm | Hash digest | |
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SHA256 | 5d69528c01746159faf814e083bb4a4fa565b80c78302bc3122f252d40d961a2 |
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MD5 | 4dccde54080a3193d8d8f12cc5039231 |
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BLAKE2b-256 | d69c5d626b4272153be931a150c13a66c94f875405637c89c88161b908c7202d |
Hashes for ClustAssessPy-1.0.1-cp39-cp39-macosx_11_0_arm64.whl
Algorithm | Hash digest | |
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SHA256 | 1757c5bb07ff169b37ea966658c3e86d6fe30a4a890ac7b1e8838aba510c3d19 |
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MD5 | c875c92a5e67a747ad4970d6ef4c979f |
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BLAKE2b-256 | d2aa6c97e50119cb2f6c6ac5d2a2091833d23730b0346f61a807e5e8f78035c2 |
Hashes for ClustAssessPy-1.0.1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 6c7c0db13feaeb644aff976f11209ba40014985218706fb9de4c29ea3a85e939 |
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MD5 | adf05bf3af4e08bb2863513292b3174e |
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BLAKE2b-256 | 51bd8c836f202e00769f1f1ff5fbda5e080395b55a1f891dd716ef3b7c05aff5 |
Hashes for ClustAssessPy-1.0.1-cp38-cp38-win_amd64.whl
Algorithm | Hash digest | |
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SHA256 | 79cdb9ff8de9d695444dfa94d71f04cd7a7f25823141931c7c7372f9c83ec086 |
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MD5 | e40fc506ac63ad445b84a9cca6cad8c8 |
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BLAKE2b-256 | 85ee4fa5c96dfe07cecb0ece8e478447a37b2525a25c74fe7cafeae98646e36f |
Hashes for ClustAssessPy-1.0.1-cp38-cp38-win32.whl
Algorithm | Hash digest | |
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SHA256 | 149d2c507959663b42004cad165f8f6e849f064f0161dbd0f54b010dca02778e |
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MD5 | fd0b3ce4c033fe9754eb3cb1133a2e01 |
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BLAKE2b-256 | 2374528b5732fcdbc1eaf5ce8207d584afa3cdc3a5e73a1ea997ea215314e57c |
Hashes for ClustAssessPy-1.0.1-cp38-cp38-musllinux_1_2_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 292b9a3883214713584043d862f39077a6fd66b99665d8d4aa00ccba2cdaee67 |
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MD5 | 0613c36136e2c9db188912314440a6b1 |
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BLAKE2b-256 | d602dabac8999705a23a0ad4932617c893d056bf7641116f815eacde404681dd |
Hashes for ClustAssessPy-1.0.1-cp38-cp38-musllinux_1_2_i686.whl
Algorithm | Hash digest | |
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SHA256 | 1274ebaccdabfaed329d4c7ce0efd59b85186d3c18aa3e427725ffe2b6bc3b07 |
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MD5 | b1abf193ec8a916910b55c7b06d9432f |
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BLAKE2b-256 | 816c2504feaa58e82fe882e12b38b06cec93236c03e4be03dbbce101238da421 |
Hashes for ClustAssessPy-1.0.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 53c5c58a43224c9c6439b859cc848ceb51369cde605a0cca88905ece41966c71 |
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MD5 | 332fb950c60a65ebb9801014c4c2305b |
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BLAKE2b-256 | 3cac2b1183f775080c3cf44233e3786c2b64af79fc62b39ced7fa85eb182988f |
Hashes for ClustAssessPy-1.0.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm | Hash digest | |
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SHA256 | 5a3d7f9cebbadc5908067e48c15383cfded1e417c79862959a6054f2c43d41ce |
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MD5 | 4c2f774266e45c4b6cec959d57a83b48 |
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BLAKE2b-256 | f2df7e22185ccbb843308d3e48496f1f0139dbff7854cfc74024d1d81dae5a08 |
Hashes for ClustAssessPy-1.0.1-cp38-cp38-macosx_11_0_arm64.whl
Algorithm | Hash digest | |
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SHA256 | 3ebc3adc5c0c4e1d2073c621a5802dd4b4152a93cdf946850cdedc82f794fb83 |
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MD5 | 5efbd8dd0cbaf38071ade093463959ba |
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BLAKE2b-256 | ac12a09413560e186c30dbcb774f8b8fdb054927f85501f2bb789110ebc92b93 |
Hashes for ClustAssessPy-1.0.1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 5c4f9f6dca72810b6e206b3764d01f96a15273afc653cb68d9c9c7ec1e8086b6 |
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MD5 | 46255e1cb20a0d12987ac96e1a3903c4 |
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BLAKE2b-256 | 20e4f21c68e1c5e64ce487d119c80a80e3923a3d75b0a57853f0a3f6b5ba4a1d |
Hashes for ClustAssessPy-1.0.1-cp37-cp37m-win_amd64.whl
Algorithm | Hash digest | |
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SHA256 | e5db4dd9c5cd4abe65857e6c401a6cb649ed086e2639b87bc5646ad5d80f9aa1 |
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MD5 | 176c6b449b636a556d4cdc12d60228a4 |
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BLAKE2b-256 | 53647ce7c0c9e0293cb0445dd662382bf0a5e476aa02d8bf35e01a27aff18452 |
Hashes for ClustAssessPy-1.0.1-cp37-cp37m-win32.whl
Algorithm | Hash digest | |
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SHA256 | 578bceeece5346fc71181f55aa870908eebf88ef05032fbd9fa64caf5b0678f7 |
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MD5 | 22985b9aec878fc5d15189c290aa8136 |
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BLAKE2b-256 | cc44734d58a20685cbe9cc2f2844c9a1c4e9a0ff7e82a412c58b21f0e071bc00 |
Hashes for ClustAssessPy-1.0.1-cp37-cp37m-musllinux_1_2_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | c50055af8b562a729f30de82369ebf0d758b99c2edd774f9908c95f7b7b1945f |
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MD5 | de146df2755a6e981319872110918aeb |
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BLAKE2b-256 | c9d77a0e20238cdb4714cb39e82f63da59b907dd9bd4ddb83bc0025bc6b8958f |
Hashes for ClustAssessPy-1.0.1-cp37-cp37m-musllinux_1_2_i686.whl
Algorithm | Hash digest | |
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SHA256 | 5c904dc60b95125bc1b8bcd6313925658f83f5dfae4577963d0688af9e6d96fd |
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MD5 | f813fd1331a0540c686f4486171c5e16 |
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BLAKE2b-256 | f6c8e4ac702fc2d2330980dc759813297931baed8c2d419d5181be4765a2204a |
Hashes for ClustAssessPy-1.0.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | d0206a9973e63a64e3657d12c81509152248e5e84a29ee52c1756d26576f743b |
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MD5 | fec8fe616261d6fcd2539049efbca8da |
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BLAKE2b-256 | 9543eec867783576a1cf0a9233426ff3ab23dc5a90ca7c6c604d0faa17d08047 |
Hashes for ClustAssessPy-1.0.1-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm | Hash digest | |
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SHA256 | 3ffcfcbd8f3fec0d9b44b7994481a1f3cbbd590b913a94de1900d48145099a5b |
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MD5 | d703ebbc4fb8a559beaebfd893f3ee8b |
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BLAKE2b-256 | bb55ab3a07fcd89746b4cce5e8c0de211bf124d76400450bba2c93e5b1dc795b |
Hashes for ClustAssessPy-1.0.1-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | ab197472de4df4d54beb014998824a239e925598502a842f5deda5f30899a62b |
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MD5 | a4128cb9a153cf557eddd886d527323e |
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BLAKE2b-256 | 34f7d39f939566bc6beda6d2ca241b757ef87373d0021110fe254666883798e4 |