prepared for buliding package

DeSide-1.0.0.dist-info/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2022 Xin Xiong
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

DeSide-1.0.0.dist-info/METADATA

@@ -0,0 +1,110 @@
+Metadata-Version: 2.1
+Name: DeSide
+Version: 1.0.0
+Summary: A DEep-learning and SIngle-cell based DEconvolution method for solid tumors
+Home-page: 
+Author: Xin (Belter) Xiong
+Author-email: OnlyBelter <[email protected]>
+License: MIT License
+
+        Copyright (c) 2022 Xin Xiong
+
+        Permission is hereby granted, free of charge, to any person obtaining a copy
+        of this software and associated documentation files (the "Software"), to deal
+        in the Software without restriction, including without limitation the rights
+        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+        copies of the Software, and to permit persons to whom the Software is
+        furnished to do so, subject to the following conditions:
+
+        The above copyright notice and this permission notice shall be included in all
+        copies or substantial portions of the Software.
+
+        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+        SOFTWARE.
+
+Project-URL: Homepage, https://github.com/OnlyBelter/DeSide
+Project-URL: Source, https://github.com/OnlyBelter/DeSide
+Project-URL: Tracker, https://github.com/OnlyBelter/DeSide/issues
+Keywords: DeSide,RNA-seq,deconvolution
+Platform: any
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Typing :: Typed
+Requires-Python: >=3.8
+Description-Content-Type: text/markdown
+License-File: LICENSE
+Requires-Dist: tensorflow (>=2.8.0)
+Requires-Dist: scikit-learn (==0.24.0)
+Requires-Dist: anndata (>=0.8.0)
+Requires-Dist: scanpy (==1.8.0)
+Requires-Dist: pandas (==1.2.5)
+Requires-Dist: numpy (<1.22)
+Requires-Dist: matplotlib
+Requires-Dist: seaborn (>=0.11.2)
+Requires-Dist: bbknn (==1.5.1)
+Requires-Dist: SciencePlots
+Provides-Extra: full
+Requires-Dist: py ; extra == 'full'
+Requires-Dist: tqdm ; extra == 'full'
+
+# DeSide <img src="./docs/_static/logo.png" width="50">
+
+DeSide is a DEep-learning and SIngle-cell based DEconvolution method for solid tumors, which can be used to infer cellular proportions of different cell types from bulk RNA-seq data.
+
+DeSide consists of the following four parts (see figure below):
+- DNN Model
+- Single Cell Dataset Integration
+- Cell Proportion Generation
+- Bulk Tumor Synthesis
+
+<img src="Fig.1a_b.svg" width="800" alt="Overview of DeSide">
+
+In this repository, we provide the code for implementing these four parts and visualizing the results.
+
+### Requirements
+DeSide requires Python 3.8 or higher. It has been tested on Linux and MacOS, but should work on Windows as well.
+- tensorflow>=2.8.0
+- scikit-learn==0.24.0
+- anndata>=0.8.0
+- scanpy==1.8.0
+- pandas==1.2.5
+- numpy<1.22
+- matplotlib
+- seaborn>=0.11.2
+- bbknn==1.5.1
+- SciencePlots
+
+### Installation
+
+pip should work out of the box:
+```
+# create a virtual environment if necessary
+conda create -n deside python=3.8
+conda activate deside
+pip install deside
+```
+
+### Documentation
+Documentation is available either in the source tree (doc/), or online. (will be available soon)
+
+
+### Usage Examples
+Usage examples can be found: [DeSide_mini_example](https://github.com/OnlyBelter/DeSide_mini_example)
+
+Three examples are provided:
+- Using pre-trained model
+- Training a model from scratch
+- Generating a synthetic dataset
+
+### License
+DeSide can be used under the terms of the MIT License.

DeSide-1.0.0.dist-info/RECORD

@@ -0,0 +1,29 @@
+deside/__init__.py,sha256=JV6-OnoUDJ-PMfn1mJ8GLBGE0VvKIchFnwDw6LHFUUs,185
+deside/bulk_cell/__init__.py,sha256=3vhYnAgxcfIa5ZA4V929TlKeBdnL417xciA3RUWZmg0,386
+deside/bulk_cell/preprocessing.py,sha256=l57cMyaic1DJzY4OT7z7PsEfO83Wh0YGnBgRiHGxDLI,12936
+deside/decon_cf/__init__.py,sha256=CmlR9iJaudBjj5h8l__ezgYC1XO6iS5sFeFgwx4Wb9s,27
+deside/decon_cf/deside.py,sha256=YJvjVgMvSEEPo7Kjggeu23IJWuttjJ11DOD0_PKyGDM,19538
+deside/plot/__init__.py,sha256=-uTTiKFWNdW3XsLEN-_ovOs2BUI3I6svW5SXq8r7n4k,1034
+deside/plot/evaluate_result.py,sha256=l_hHQpODMsfgUeGYjU-ZAAtT7fy8Yv7ogn04nnO8dQ8,36060
+deside/plot/plot_clustering.py,sha256=yDJaBJzifJDEjO6SgaCWnxr_sYq90wyKYHtyEvk4n_0,11225
+deside/plot/plot_gene.py,sha256=ksAXng_jG6N05we2kRkpPckjmDu7NxGlBVTkhZn13uk,24932
+deside/plot/plot_nn.py,sha256=QNG1o6lf7xQBQWtq_uSi2yvZR4FXOsSxb7mPGCSVRG8,14207
+deside/plot/plot_sample.py,sha256=x_EJyCkcPPMgEhzNn6TI62H34KxcKGaoaYMWinle-hI,2368
+deside/simulation/__init__.py,sha256=ek4UglWTI7ulUlherKTAC0nq1nnZdXnxRM_MSYv-Dn4,399
+deside/simulation/generate_data.py,sha256=wvF9tqD_f8fcYSMxLbHFdjX2szD2GmCn5qHjdcuztGc,88598
+deside/simulation/stats_test.py,sha256=OyZ0YK9vrL1lnbrc5p85fswc3jMnrNeNhm1uoBicHVE,2764
+deside/single_cell/__init__.py,sha256=TPM67JrK7NkYknpDbE4Flx0Jp7rO0pL4RlHEO6_mc0Y,355
+deside/single_cell/preprocessing.py,sha256=QRjJ6FG2KRm4f34eF-lHZ6m0Aw1qxfnv7bYJYEu5-kI,37134
+deside/utility/__init__.py,sha256=CryOoBpoaTTssxvcBOh8llrc7tVK1bNrZYg_yvZQ3ao,5199
+deside/utility/compare.py,sha256=pGwrOpdRVUdng_OXK1A-aiAarbVpITyLeTuGECorFtI,14535
+deside/utility/core_obj.py,sha256=Pu76BWblQOoOL6bd_gTT4PwtU8Vy3vwmgMu-ShtGMNw,6919
+deside/utility/evaluation.py,sha256=t7egOgiI2oBOi6sndQqyZsAPWDkxI-yo30x5T7bzRh8,1337
+deside/utility/pub_func.py,sha256=4MdRFPg78q7Pg1rcKUEFeaPAPbVPypJAlS0-dDmgw5I,39996
+deside/utility/read_file.py,sha256=RxaZy4ib6_OzbX_4b619Idph_Md0tGx2pkXKMSlz_xE,14824
+deside/workflow/__init__.py,sha256=kn8t1Cmcj-GD3EvCNXg2mMAA904BpfC_Gm2MeKusJh4,130
+deside/workflow/workflow.py,sha256=deQ7fG8mC9ykd5bdT4LlEMGvGss3z4yEy0lG1JbGVjE,15411
+DeSide-1.0.0.dist-info/LICENSE,sha256=a8EO2KtToqJJuEhq-W3NMv2lhnAZ9LTCV-CZ8AnUXF8,1087
+DeSide-1.0.0.dist-info/METADATA,sha256=FoUs4okhP7W5lwSk_xec4w_R46VGfOea4DpBaFP2I7U,4053
+DeSide-1.0.0.dist-info/WHEEL,sha256=pkctZYzUS4AYVn6dJ-7367OJZivF2e8RA9b_ZBjif18,92
+DeSide-1.0.0.dist-info/top_level.txt,sha256=5fQgOaSHTjnED8bXP41-6MUhGmejWhAmqhXFhIQKaPI,7
+DeSide-1.0.0.dist-info/RECORD,,

DeSide-1.0.0.dist-info/WHEEL

@@ -0,0 +1,5 @@
+Wheel-Version: 1.0
+Generator: bdist_wheel (0.40.0)
+Root-Is-Purelib: true
+Tag: py3-none-any
+

DeSide-1.0.0.dist-info/top_level.txt

@@ -0,0 +1 @@
+deside

MANIFEST.in

@@ -0,0 +1,2 @@
+include Fig.1a_b.svg
+include docs/*

README.md

@@ -1,4 +1,4 @@
-# DeSide <img src="./docs/_static/logo.png" width="50">
+# DeSide <img src="https://raw.githubusercontent.com/OnlyBelter/DeSide/main/docs/_static/logo.png" width="50">
 
 DeSide is a DEep-learning and SIngle-cell based DEconvolution method for solid tumors, which can be used to infer cellular proportions of different cell types from bulk RNA-seq data.
 
@@ -8,7 +8,7 @@ DeSide consists of the following four parts (see figure below):
 - Cell Proportion Generation
 - Bulk Tumor Synthesis
 
-<img src="Fig.1a_b.svg" width="800" alt="Overview of DeSide">
+<img src="https://raw.githubusercontent.com/OnlyBelter/DeSide/main/Fig.1a_b.svg" width="800" alt="Overview of DeSide">
 
 In this repository, we provide the code for implementing these four parts and visualizing the results.
 

pyproject.toml

@@ -0,0 +1,77 @@
+# pyproject.toml
+
+[build-system]
+requires = ["setuptools>=61.0.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "DeSide"
+version = "1.0.1"
+description = "A DEep-learning and SIngle-cell based DEconvolution method for solid tumors"
+readme = "README.md"
+license = { file = "LICENSE" }
+requires-python = ">=3.8"
+authors = [
+    { name = "OnlyBelter", email = "[email protected]" },
+]
+keywords = [
+    "DeSide",
+    "RNA-seq",
+    "deconvolution",
+]
+classifiers = [
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: BSD License",
+    "Programming Language :: Python",
+    "Programming Language :: Python :: 3.8",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Typing :: Typed",
+]
+dependencies = [
+    "tensorflow>=2.8.0",
+    "scikit-learn==0.24.0",
+    "anndata>=0.8.0",
+    "scanpy==1.8.0",
+    "pandas==1.2.5",
+    "numpy<1.22",
+    "matplotlib",
+    "seaborn>=0.11.2",
+    "bbknn==1.5.1",
+    "SciencePlots",
+]
+#dynamic = ["version"]
+
+[project.urls]
+#Documentation = "https://deside.readthedocs.io/"
+Homepage = "https://github.com/OnlyBelter/DeSide"
+Source = "https://github.com/OnlyBelter/DeSide"
+Tracker = "https://github.com/OnlyBelter/DeSide/issues"
+
+# https://realpython.com/pypi-publish-python-package/#version-your-package
+[tool.bumpver]
+current_version = "1.0.0"
+version_pattern = "MAJOR.MINOR.PATCH"
+commit_message = "bump version {old_version} -> {new_version}"
+commit = true
+tag = true
+push = false
+
+[tool.bumpver.file_patterns]
+"pyproject.toml" = [
+    'current_version = "{version}"',
+]
+"setup.py" = [
+    "{version}",
+    "{pep440_version}",
+]
+"README.rst" = [
+    "{version}",
+    "{pep440_version}",
+]
+"README.md" = [
+    "{version}",
+    "{pep440_version}",
+]
+

setup.py

@@ -2,21 +2,22 @@
 import os
 import sys
 from setuptools import setup, find_packages
+# from deside._version import __version__
 
 install_requires = ["matplotlib", "pandas==1.2.5", "scikit-learn==0.24.0",
                     "seaborn>=0.11.2", "requests", "tensorflow>=2.8.0", "scipy", "numpy<1.22",
                     "anndata>=0.8.0", "scanpy==1.8.0", "joblib", "leidenalg", "jupyterlab",
                     "umap-learn==0.5.1", "bbknn==1.5.1", "openpyxl", "tensorboard",
-                    "build", "sphinx==3.5.4", "myst-parser==0.13.6", "fsspec",
+                    "build", "sphinx==3.5.4", "myst-parser>=0.13.6", "fsspec",
                     "h5py", "sphinx_book_theme", "tables>=3.6.1", "statsmodels", "matplotlib-venn",
                     "SciencePlots"]
 if sys.version_info < (3, 4, 0):
     install_requires.append("enum34")
 
 
-def get_version():
-    with open(os.path.join("deside", "_version.txt"), 'r') as f:
-        return f.readline().strip()
+# def get_version():
+#     with open(os.path.join("deside", "_version.txt"), 'r') as f:
+#         return f.readline().strip()
 
 
 def get_test_data():
@@ -34,7 +35,7 @@ def get_test_data():
 
 setup(
     name="deside",
-    version=get_version(),
+    version='1.0.0',
     description="DEep-learning and SIngle-cell based DEconvolution",
     long_description=README_rst,
     license="BSD-3-Clause",