COSCST

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0.1 COSCST-0.1-py3-none-any.whl

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Project: COSCST
Version: 0.1
Filename: COSCST-0.1-py3-none-any.whl
Download: [link]
Size: 21361
MD5: abbe4a022822d0b820131ccecf22f5ca
SHA256: c209bb6e4d0edd7ff59bc833283c6c7608de26c42357a91b755f6b91c0d8565f
Uploaded: 2024-04-01 03:11:30 +0000

dist-info

METADATA

Metadata-Version: 2.1
Name: COSCST
Version: 0.1
Summary: Single-cell RNA sequencing data excels in providing high sequencing depth and precision at the single-cell level, but lacks spatial information. Simultaneously, spatial transcriptomics technology visualizes gene expression patterns in their spatial context but has low resolution. Here, we present COSCST that combines these two datasets through autoencoder and supervised learning model to map single-cell RNA-seq data with spatial coordination and spatial transcriptomics with precise cell type annotation.
Author: Yi Shi, Gang Hu
Author-Email: shiyi[at]nankai.mail.edu.cn, huggs[at]nankai.edu.cn
Home-Page: https://github.com/shiy-shiy/SCST/
Download-Url: https://github.com/shiy-shiy/SCST/archive/refs/heads/main.zip
License: MIT
Keywords: single cell,spatial transcriptome
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Dist: matplotlib (>=2.2)
Requires-Dist: tensorflow
Requires-Dist: scanpy
Requires-Dist: louvain
Requires-Dist: python-igraph
Requires-Dist: h5py
Requires-Dist: pandas
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WHEEL

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RECORD

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COSCST/__init__.py sha256=BoEykA4-TRbsRi06YbUyPM7T0xgtZMaiMQj9xKEoMeQ 28
COSCST/coscst.py sha256=fuUnEpVfdmUbG2p6iSEr7ECgjEZ06FOBay0aPKzIZ_w 20133
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COSCST-0.1.dist-info/RECORD

top_level.txt

COSCST