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eleozzr / desc

Deep Embedding for Single-cell Clustering
https://eleozzr.github.io/desc/
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Can not get same results from tutorial desc_2.1.1_paul.ipynb #39

Open ichobits opened 3 years ago

ichobits commented 3 years ago

I can not get the same results from the tutorial desc_2.1.1_paul.ipynb and desc_2.0.3_paul.ipynb. https://eleozzr.github.io/desc/tutorial.html

my desc_2.1.1 env: conda create the python==3.6.13

Name Version Build
absl-py 0.12.0 pypi_0
anndata 0.7.5 pypi_0
anyio 2.2.0 py36ha15d459_0
argon2-cffi 20.1.0 py36h68aa20f_2
astunparse 1.6.3 pypi_0
async_generator 1.1 py_0
attrs 20.3.0 pyhd3deb0d_0
babel 2.9.0 pyhd3deb0d_0
backports 1 py_2
backports.functools_lru_cache 1.6.3 pyhd8ed1ab_0
bleach 3.3.0 pyh44b312d_0
cached-property 1.5.2 pypi_0
cachetools 4.2.1 pypi_0
certifi 2020.12.5 py36ha15d459_1
cffi 1.14.5 py36he58ceb7_0
chardet 4.0.0 pypi_0
click 7.1.2 pypi_0
colorama 0.4.4 pyh9f0ad1d_0
contextvars 2.4 py_0
cycler 0.10.0 pypi_0
dataclasses 0.8 pyh787bdff_0
decorator 4.4.2 pypi_0
defusedxml 0.7.1 pyhd8ed1ab_0
desc 2.1.1 pypi_0
entrypoints 0.3 pyhd8ed1ab_1003
flatbuffers 1.12 pypi_0
gast 0.3.3 pypi_0
get-version 2.1 pypi_0
google-auth 1.28.0 pypi_0
google-auth-oauthlib 0.4.4 pypi_0
google-pasta 0.2.0 pypi_0
grpcio 1.32.0 pypi_0
h5py 2.10.0 pypi_0
idna 2.1 pypi_0
immutables 0.15 py36h68aa20f_0
importlib-metadata 3.10.0 py36ha15d459_0
ipykernel 5.5.3 py36hfacbf0b_0
ipython 5.8.0 py36_1
ipython_genutils 0.2.0 py_1
jinja2 2.11.3 pyh44b312d_0
joblib 1.0.1 pypi_0
json5 0.9.5 pyh9f0ad1d_0
jsonschema 3.2.0 pyhd8ed1ab_3
jupyter-packaging 0.7.12 pyhd8ed1ab_0
jupyter_client 6.1.12 pyhd8ed1ab_0
jupyter_core 4.7.1 py36ha15d459_0
jupyter_server 1.5.1 py36ha15d459_0
jupyterlab 3.0.12 pyhd8ed1ab_0
jupyterlab_pygments 0.1.2 pyh9f0ad1d_0
jupyterlab_server 2.4.0 pyhd8ed1ab_0
keras-preprocessing 1.1.2 pypi_0
kiwisolver 1.3.1 pypi_0
legacy-api-wrap 1.2 pypi_0
libsodium 1.0.18 h8d14728_1
llvmlite 0.36.0 pypi_0
m2w64-gcc-libgfortran 5.3.0 6
m2w64-gcc-libs 5.3.0 7
m2w64-gcc-libs-core 5.3.0 7
m2w64-gmp 6.1.0 2
m2w64-libwinpthread-git 5.0.0.4634.697f757 2
markdown 3.3.4 pypi_0
markupsafe 1.1.1 py36h68aa20f_3
matplotlib 3.3.4 pypi_0
mistune 0.8.4 py36h68aa20f_1003
msys2-conda-epoch 20160418 1
natsort 7.1.1 pypi_0
nbclassic 0.2.6 pyhd8ed1ab_0
nbclient 0.5.3 pyhd8ed1ab_0
nbconvert 6.0.7 py36ha15d459_3
nbformat 5.1.3 pyhd8ed1ab_0
nest-asyncio 1.5.1 pyhd8ed1ab_0
networkx 2.5.1 pypi_0
notebook 6.3.0 py36ha15d459_0
numba 0.53.1 pypi_0
numexpr 2.7.3 pypi_0
numpy 1.19.5 pypi_0
oauthlib 3.1.0 pypi_0
opt-einsum 3.3.0 pypi_0
packaging 20.9 pyh44b312d_0
pandas 1.1.5 pypi_0
pandoc 2.13 h8ffe710_0
pandocfilters 1.4.2 py_1
patsy 0.5.1 pypi_0
pickleshare 0.7.5 py_1003
pillow 8.2.0 pypi_0
pip 21.0.1 pyhd8ed1ab_0
prometheus_client 0.10.0 pyhd8ed1ab_0
prompt_toolkit 1.0.15 py_1
protobuf 3.15.7 pypi_0
pyasn1 0.4.8 pypi_0
pyasn1-modules 0.2.8 pypi_0
pycparser 2.2 pyh9f0ad1d_2
pydot 1.4.2 pypi_0
pygments 2.8.1 pyhd8ed1ab_0
pynndescent 0.5.2 pypi_0
pyparsing 2.4.7 pyh9f0ad1d_0
pyrsistent 0.17.3 py36h68aa20f_2
python 3.6.13 h39d44d4_0_cpython
python-dateutil 2.8.1 py_0
python_abi 3.6 1_cp36m
pytz 2021.1 pyhd8ed1ab_0
pywin32 300 py36h68aa20f_0
pywinpty 0.5.7 py36h9f0ad1d_1
pyzmq 22.0.3 py36h1d5d788_1
requests 2.25.1 pypi_0
requests-oauthlib 1.3.0 pypi_0
rsa 4.7.2 pypi_0
scanpy 1.5.1 pypi_0
scikit-learn 0.24.1 pypi_0
scipy 1.5.4 pypi_0
seaborn 0.11.1 pypi_0
send2trash 1.5.0 py_0
setuptools 54.2.0 pypi_0
setuptools-scm 6.0.1 pypi_0
simplegeneric 0.8.1 py_1
six 1.15.0 pyh9f0ad1d_0
sniffio 1.2.0 py36ha15d459_1
statsmodels 0.12.2 pypi_0
stdlib-list 0.8.0 pypi_0
tables 3.6.1 pypi_0
tensorboard 2.4.1 pypi_0
tensorboard-plugin-wit 1.8.0 pypi_0
tensorflow 2.4.1 pypi_0
tensorflow-estimator 2.4.0 pypi_0
termcolor 1.1.0 pypi_0
terminado 0.9.4 py36ha15d459_0
testpath 0.4.4 py_0
texttable 1.6.3 pypi_0
threadpoolctl 2.1.0 pypi_0
tornado 6.1 py36h68aa20f_1
tqdm 4.60.0 pypi_0
traitlets 4.3.3 py36h9f0ad1d_1
typing_extensions 3.7.4.3 py_0
umap-learn 0.5.1 pypi_0
urllib3 1.26.4 pypi_0
vc 14.2 hb210afc_4
vs2015_runtime 14.28.29325 h5e1d092_4
wcwidth 0.2.5 pyh9f0ad1d_2
webencodings 0.5.1 py_1
werkzeug 1.0.1 pypi_0
wheel 0.36.2 pyhd3deb0d_0
wincertstore 0.2 py36ha15d459_1006
winpty 0.4.3 4
wrapt 1.12.1 pypi_0
zeromq 4.3.4 h0e60522_0
zipp 3.4.1 pyhd8ed1ab_0

Then, I follow the tutorial desc_2.1.1_paul.ipynb.

1.different cell matrix

desc_2.1.1_paul.ipynb. AnnData object with n_obs × n_vars = 2730 × 999 obs: 'paul15_clusters', 'celltype', 'celltype2', 'desc_0.8', 'desc_1.0' var: 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'mean', 'std' uns: 'iroot', 'log1p', 'prob_matrix0.8', 'prob_matrix1.0' obsm: 'X_Embeded_z0.8', 'X_tsne', 'X_tsne0.8', 'X_Embeded_z1.0', 'X_tsne1.0'

my script: AnnData object with n_obs × n_vars = 2730 × 1000 obs: 'paul15_clusters', 'celltype', 'celltype2', 'desc_0.8', 'desc_1.0' var: 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'mean', 'std' uns: 'iroot', 'log1p', 'prob_matrix0.8', 'prob_matrix1.0' obsm: 'X_Embeded_z0.8', 'X_tsne', 'X_tsne0.8', 'X_Embeded_z1.0', 'X_tsne1.0'

2.different t-sen picture desc_2.1.1_paul.ipynb. https://ibb.co/GsPv38j

my script: https://ibb.co/NxhHgq0

What is the cause of these differences?

eleozzr commented 3 years ago

Maybe due to the version of scanpy. Sometimes scanpy cannot exactly identify 1000 hvgs even you set n_hvg=1000.