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Starlitnightly / omicverse

A python library for multi omics included bulk, single cell and spatial RNA-seq analysis.
https://starlitnightly.github.io/omicverse/
GNU General Public License v3.0
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error in running run T-DESEQ2 in bulk RNA sequencing analysis. #151

Open yanbosmu opened 1 month ago

yanbosmu commented 1 month ago

# When I run T-DESEQ2 in bulk RNA sequencing analysis.

treatment_groups=['4-3','4-4'] control_groups=['1--1','1--2'] result=dds.deg_analysis(treatment_groups,control_groups,method='DEseq2')

Fitting size factors... ... done in 0.00 seconds.

Fitting dispersions... ... done in 1.99 seconds.

Fitting dispersion trend curve... ... done in 2.19 seconds.

Fitting MAP dispersions...

logres_prior=1.1516258223789004, sigma_prior=0.25

... done in 2.47 seconds.

Fitting LFCs... ... done in 2.92 seconds.

ValueError Traceback (most recent call last) Cell In[9], line 3 1 treatment_groups=['4-3','4-4'] 2 control_groups=['1--1','1--2'] ----> 3 result=dds.deg_analysis(treatment_groups,control_groups,method='DEseq2')

File /data/Conda_envs/your_path/omicverse/lib/python3.10/site-packages/omicverse/bulk/_Deseq2.py:609, in pyDEG.deg_analysis(self, group1, group2, method, alpha, multipletests_method, n_cpus, cooks_filter, independent_filter) 606 dds.calculate_cooks() 607 if dds.refit_cooks: 608 # Replace outlier counts --> 609 dds.refit() 610 stat_res = DeseqStats(dds, alpha=alpha, cooks_filter=cooks_filter, independent_filter=independent_filter) 611 stat_res.run_wald_test()

File /data/Conda_envs/your_path/omicverse/lib/python3.10/site-packages/pydeseq2/dds.py:773, in DeseqDataSet.refit(self) 767 """Refit Cook outliers. 768 769 Replace values that are filtered out based on the Cooks distance with imputed 770 values, and then re-run the whole DESeq2 pipeline on replaced values. 771 """ 772 # Replace outlier counts --> 773 self._replace_outliers() 774 if not self.quiet: 775 print( 776 f"Refitting {sum(self.varm['replaced']) } outliers.\n", file=sys.stderr 777 )

File /data/Conda_envs/your_path/omicverse/lib/python3.10/site-packages/pydeseq2/dds.py:863, in DeseqDataSet._replace_outliers(self) 854 n_or_more = ( 855 self.obsm["design_matrix"][ 856 self.obsm["design_matrix"].columns[-1] 857 ].value_counts() 858 >= self.min_replicates 859 ) 861 if n_or_more.sum() == 0: 862 # No sample can be replaced. Set self.replaced to False and exit. --> 863 self.varm["replaced"] = pd.Series(False, index=self.var_names) 864 return 866 replaceable = n_or_more[ 867 self.obsm["design_matrix"][self.obsm["design_matrix"].columns[-1]] 868 ]

File /data/Conda_envs/your_path/omicverse/lib/python3.10/site-packages/anndata/_core/aligned_mapping.py:216, in AlignedActual.setitem(self, key, value) 215 def setitem(self, key: str, value: Value): --> 216 value = self._validate_value(value, key) 217 self._data[key] = value

File /data/Conda_envs/your_path/omicverse/lib/python3.10/site-packages/anndata/_core/aligned_mapping.py:279, in AxisArraysBase._validate_value(self, val, key) 277 msg = "Index.equals and pd.testing.assert_index_equal disagree" 278 raise AssertionError(msg) --> 279 return super()._validate_value(val, key)

File /data/Conda_envs/your_path/omicverse/lib/python3.10/site-packages/anndata/_core/aligned_mapping.py:100, in AlignedMappingBase._validate_value(self, val, key) 97 raise ValueError(msg) 99 name = f"{self.attrname.title().rstrip('s')} {key!r}" --> 100 return coerce_array(val, name=name, allow_df=self._allow_df)

File /data/Conda_envs/your_path/omicverse/lib/python3.10/site-packages/anndata/_core/storage.py:104, in coerce_array(value, name, allow_df, allow_array_like) 102 if e is not None: 103 msg += " (Failed to convert it to an array, see above for details.)" --> 104 raise ValueError(msg) from e

ValueError: Varm 'replaced' needs to be of one of np.ndarray, numpy.ma.core.MaskedArray, scipy.sparse.spmatrix, awkward.Array, h5py.Dataset, zarr.Array, zappy.base.ZappyArray, anndata.experimental.[CSC,CSR]Dataset, dask.array.Array, cupy.ndarray, or cupyx.scipy.sparse.spmatrix, not <class 'pandas.core.series.Series'>.

Any solution to this? OMICVERSE 1.6.5

yanbosmu commented 1 month ago

packages in environment at /data/Conda_envs/your_path/omicverse:

#

Name Version Build Channel

_libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 2_kmp_llvm conda-forge _sysroot_linux-64_curr_repodata_hack 3 h69a702a_16 conda-forge absl-py 2.1.0 pyhd8ed1ab_0 conda-forge adjusttext 1.2.0 pyhd8ed1ab_0 conda-forge aiohappyeyeballs 2.4.0 pyhd8ed1ab_0 conda-forge aiohttp 3.10.5 py310h5b4e0ec_0 conda-forge aiosignal 1.3.1 pyhd8ed1ab_0 conda-forge anndata 0.10.9 pyhd8ed1ab_0 conda-forge anyio 4.4.0 pyhd8ed1ab_0 conda-forge aom 3.9.1 hac33072_0 conda-forge appdirs 1.4.4 pyh9f0ad1d_0 conda-forge argon2-cffi 23.1.0 pyhd8ed1ab_0 conda-forge argon2-cffi-bindings 21.2.0 py310h2372a71_4 conda-forge arpack 3.9.1 nompi_h77f6705_101 conda-forge array-api-compat 1.8 pyhd8ed1ab_0 conda-forge arrow 1.3.0 pyhd8ed1ab_0 conda-forge ase 3.23.0 pyhd8ed1ab_0 conda-forge astor 0.8.1 pyh9f0ad1d_0 conda-forge asttokens 2.4.1 pyhd8ed1ab_0 conda-forge async-lru 2.0.4 pyhd8ed1ab_0 conda-forge async-timeout 4.0.3 pyhd8ed1ab_0 conda-forge atk-1.0 2.38.0 hd4edc92_1 conda-forge attrs 24.2.0 pyh71513ae_0 conda-forge autograd 1.6.2 pyhd8ed1ab_0 conda-forge autograd-gamma 0.5.0 pyh9f0ad1d_0 conda-forge aws-c-auth 0.7.20 h5f1c8d9_0 conda-forge aws-c-cal 0.6.12 h2ba76a8_0 conda-forge aws-c-common 0.9.17 h4ab18f5_0 conda-forge aws-c-compression 0.2.18 h36a0aea_4 conda-forge aws-c-event-stream 0.4.2 h161de36_10 conda-forge aws-c-http 0.8.1 h63f54a0_13 conda-forge aws-c-io 0.14.8 h96d4d28_0 conda-forge aws-c-mqtt 0.10.4 hcc7299c_2 conda-forge aws-c-s3 0.5.9 h10bd90f_0 conda-forge aws-c-sdkutils 0.1.16 h36a0aea_0 conda-forge aws-checksums 0.1.18 h36a0aea_4 conda-forge aws-crt-cpp 0.26.8 h4f3a3cc_11 conda-forge aws-sdk-cpp 1.11.267 h51dfee4_8 conda-forge babel 2.14.0 pyhd8ed1ab_0 conda-forge beautifulsoup4 4.12.3 pyha770c72_0 conda-forge biopython 1.78 pypi_0 pypi bioservices 1.11.2 pypi_0 pypi bleach 6.1.0 pyhd8ed1ab_0 conda-forge blinker 1.8.2 pyhd8ed1ab_0 conda-forge blosc 1.21.5 hc2324a3_1 conda-forge bokeh 3.4.2 pyhd8ed1ab_0 conda-forge boltons 24.0.0 pyhd8ed1ab_0 conda-forge branca 0.7.2 pyhd8ed1ab_0 conda-forge brotli 1.1.0 hd590300_1 conda-forge brotli-bin 1.1.0 hd590300_1 conda-forge brotli-python 1.1.0 py310hc6cd4ac_1 conda-forge bzip2 1.0.8 h4bc722e_7 conda-forge c-ares 1.33.1 heb4867d_0 conda-forge ca-certificates 2024.8.30 hbcca054_0 conda-forge cached-property 1.5.2 hd8ed1ab_1 conda-forge cached_property 1.5.2 pyha770c72_1 conda-forge cachetools 5.5.0 pyhd8ed1ab_0 conda-forge cairo 1.18.0 h3faef2a_0 conda-forge captum 0.6.0 pyhd8ed1ab_0 conda-forge cattrs 22.2.0 pypi_0 pypi certifi 2024.7.4 pyhd8ed1ab_0 conda-forge cffi 1.17.0 py310h8deb56e_1 conda-forge cfitsio 4.3.1 hbdc6101_0 conda-forge chardet 5.2.0 py310hff52083_2 conda-forge charset-normalizer 3.3.2 pyhd8ed1ab_0 conda-forge chex 0.1.83 pyhd8ed1ab_0 conda-forge click 8.1.7 unix_pyh707e725_0 conda-forge cloudpickle 3.0.0 pyhd8ed1ab_0 conda-forge colorama 0.4.6 pyhd8ed1ab_0 conda-forge colorcet 3.1.0 pyhd8ed1ab_0 conda-forge colorlog 6.8.2 pypi_0 pypi comm 0.2.2 pyhd8ed1ab_0 conda-forge contextlib2 21.6.0 pyhd8ed1ab_0 conda-forge contourpy 1.3.0 py310h3788b33_0 conda-forge ctxcore 0.2.0 pypi_0 pypi cubinlinker 0.3.0 py310hfdf336d_1 rapidsai cucim 24.02.00 cuda11_py310_240212_g7d08ffc_0 rapidsai cuda-cudart 11.8.89 0 nvidia cuda-cupti 11.8.87 0 nvidia cuda-libraries 11.8.0 0 nvidia cuda-nvrtc 11.8.89 0 nvidia cuda-nvtx 11.8.86 0 nvidia cuda-profiler-api 11.8.86 0 nvidia cuda-python 11.8.3 py310hf9913ef_0 nvidia cuda-runtime 11.8.0 0 nvidia cuda-version 11.8 h70ddcb2_3 conda-forge cudatoolkit 11.8.0 h4ba93d1_13 conda-forge cudf 24.02.02 cuda11_py310_240227_gdd34fdbe35_0 rapidsai cudf_kafka 24.02.02 cuda11_py310_240227_gdd34fdbe35_0 rapidsai cudnn 8.9.7.29 hbc23b4c_3 conda-forge cugraph 24.02.00 cuda11_py310_240213_g3e5f47d0f_0 rapidsai cuml 24.02.00 cuda11_py310_240213_geb50e481d_0 rapidsai cuproj 24.02.00 cuda11_py310_240213_ga881c4a5_0 rapidsai cupy 13.3.0 py310h189a05f_0 conda-forge cupy-cuda11x 13.3.0 pypi_0 pypi cusparselt 0.5.0.1 hd5ab71f_1 conda-forge cuspatial 24.02.00 cuda11_py310_240213_ga881c4a5_0 rapidsai custreamz 24.02.02 cuda11_py310_240227_gdd34fdbe35_0 rapidsai cutensor 2.0.2.5 hee583db_0 conda-forge cuxfilter 24.02.00 cuda11_py310_240213_g4a431d7_0 rapidsai cycler 0.12.1 pyhd8ed1ab_0 conda-forge cyrus-sasl 2.1.27 h54b06d7_7 conda-forge cython 3.0.11 pypi_0 pypi cytoolz 0.12.3 py310h2372a71_0 conda-forge dask 2024.1.1 pyhd8ed1ab_0 conda-forge dask-core 2024.1.1 pyhd8ed1ab_0 conda-forge dask-cuda 24.02.00 py310_240212_g96bedbc_0 rapidsai dask-cudf 24.02.02 cuda11_py310_240227_gdd34fdbe35_0 rapidsai datashader 0.16.3 pyhd8ed1ab_0 conda-forge datetime 4.5 pypi_0 pypi dav1d 1.2.1 hd590300_0 conda-forge debugpy 1.8.5 py310hea249c9_0 conda-forge decorator 5.1.1 pyhd8ed1ab_0 conda-forge decoupler 1.8.0 pypi_0 pypi defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge deprecated 1.2.14 pypi_0 pypi dill 0.3.8 pyhd8ed1ab_0 conda-forge distributed 2024.1.1 pyhd8ed1ab_0 conda-forge dlpack 0.5 h9c3ff4c_0 conda-forge dm-tree 0.1.8 py310ha8c1f0e_4 conda-forge docrep 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conda-forge fqdn 1.5.1 pyhd8ed1ab_0 conda-forge freetype 2.12.1 h267a509_2 conda-forge freetype-py 2.3.0 pyhd8ed1ab_0 conda-forge freexl 2.0.0 h743c826_0 conda-forge fribidi 1.0.10 h36c2ea0_0 conda-forge frozendict 2.4.4 pypi_0 pypi frozenlist 1.4.1 py310h2372a71_0 conda-forge fsspec 2024.6.1 pyhff2d567_0 conda-forge future 1.0.0 pyhd8ed1ab_0 conda-forge gdal 3.8.1 py310haaa150b_3 conda-forge gdk-pixbuf 2.42.10 h829c605_5 conda-forge gdown 5.2.0 pyhd8ed1ab_0 conda-forge geopandas 1.0.1 pyhd8ed1ab_0 conda-forge geopandas-base 1.0.1 pyha770c72_0 conda-forge geos 3.12.1 h59595ed_0 conda-forge geotiff 1.7.1 hf074850_14 conda-forge get-annotations 0.1.2 pyhd8ed1ab_0 conda-forge gettext 0.22.5 he02047a_3 conda-forge gettext-tools 0.22.5 he02047a_3 conda-forge gevent 24.2.1 pypi_0 pypi gflags 2.2.2 he1b5a44_1004 conda-forge giflib 5.2.2 hd590300_0 conda-forge glog 0.7.1 hbabe93e_0 conda-forge glpk 5.0 h445213a_0 conda-forge gmock 1.15.2 ha770c72_0 conda-forge gmp 6.3.0 hac33072_2 conda-forge 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conda-forge igraph 0.10.13 hef0740d_0 conda-forge imagecodecs-lite 2019.12.3 py310h261611a_8 conda-forge imageio 2.35.1 pyh12aca89_0 conda-forge importlib-metadata 8.4.0 pyha770c72_0 conda-forge importlib_metadata 8.4.0 hd8ed1ab_0 conda-forge importlib_resources 6.4.4 pyhd8ed1ab_0 conda-forge inflect 7.3.1 pypi_0 pypi interface_meta 1.3.0 pyhd8ed1ab_0 conda-forge ipykernel 6.29.5 pyh3099207_0 conda-forge ipython 8.26.0 pyh707e725_0 conda-forge ipywidgets 8.1.5 pyhd8ed1ab_0 conda-forge isodate 0.6.1 pyhd8ed1ab_0 conda-forge isoduration 20.11.0 pyhd8ed1ab_0 conda-forge itsdangerous 2.2.0 pyhd8ed1ab_0 conda-forge jax 0.4.27 pyhd8ed1ab_0 conda-forge jaxlib 0.4.23 cuda118py310hd0f2884_202 conda-forge jaxopt 0.8.3 pyhd8ed1ab_0 conda-forge jbig 2.1 h7f98852_2003 conda-forge jedi 0.19.1 pyhd8ed1ab_0 conda-forge jinja2 3.1.4 pyhd8ed1ab_0 conda-forge joblib 1.4.2 pyhd8ed1ab_0 conda-forge json-c 0.17 h1220068_1 conda-forge json5 0.9.25 pyhd8ed1ab_0 conda-forge jsonpointer 3.0.0 py310hff52083_0 conda-forge jsonschema 4.23.0 pyhd8ed1ab_0 conda-forge jsonschema-specifications 2023.12.1 pyhd8ed1ab_0 conda-forge jsonschema-with-format-nongpl 4.23.0 hd8ed1ab_0 conda-forge jupyter-lsp 2.2.5 pyhd8ed1ab_0 conda-forge jupyter-server-proxy 4.4.0 pyhd8ed1ab_0 conda-forge jupyter_client 8.6.2 pyhd8ed1ab_0 conda-forge jupyter_core 5.7.2 py310hff52083_0 conda-forge jupyter_events 0.10.0 pyhd8ed1ab_0 conda-forge jupyter_server 2.14.2 pyhd8ed1ab_0 conda-forge jupyter_server_terminals 0.5.3 pyhd8ed1ab_0 conda-forge jupyterlab 4.2.5 pyhd8ed1ab_0 conda-forge jupyterlab_pygments 0.3.0 pyhd8ed1ab_1 conda-forge jupyterlab_server 2.27.3 pyhd8ed1ab_0 conda-forge jupyterlab_widgets 3.0.13 pyhd8ed1ab_0 conda-forge kealib 1.5.3 hee9dde6_1 conda-forge kernel-headers_linux-64 3.10.0 h4a8ded7_16 conda-forge keyutils 1.6.1 h166bdaf_0 conda-forge kiwisolver 1.4.5 py310h3788b33_2 conda-forge krb5 1.21.3 h659f571_0 conda-forge ktplotspy 0.2.4 pypi_0 pypi lazy-loader 0.4 pyhd8ed1ab_1 conda-forge lazy_loader 0.4 pyhd8ed1ab_1 conda-forge lcms2 2.16 hb7c19ff_0 conda-forge ld_impl_linux-64 2.40 hf3520f5_7 conda-forge legacy-api-wrap 1.4 pyhd8ed1ab_1 conda-forge leidenalg 0.10.2 py310hc6cd4ac_0 conda-forge lerc 4.0.0 h27087fc_0 conda-forge libabseil 20240116.2 cxx17_he02047a_1 conda-forge libaec 1.1.3 h59595ed_0 conda-forge libarchive 3.7.4 hfca40fe_0 conda-forge libarrow 14.0.2 hefa796f_19_cpu conda-forge libarrow-acero 14.0.2 hbabe93e_19_cpu conda-forge libarrow-dataset 14.0.2 hbabe93e_19_cpu conda-forge libarrow-flight 14.0.2 hc4f8a93_19_cpu conda-forge libarrow-flight-sql 14.0.2 he4f5ca8_19_cpu conda-forge libarrow-gandiva 14.0.2 hc1954e9_19_cpu conda-forge libarrow-substrait 14.0.2 he4f5ca8_19_cpu conda-forge libasprintf 0.22.5 he8f35ee_3 conda-forge libasprintf-devel 0.22.5 he8f35ee_3 conda-forge libavif16 1.1.1 h104a339_1 conda-forge libblas 3.9.0 20_linux64_openblas conda-forge libboost 1.84.0 hba137d9_3 conda-forge libboost-headers 1.86.0 ha770c72_1 conda-forge libboost-python 1.84.0 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Note: you may need to restart the kernel to use updated packages.

Starlitnightly commented 1 month ago

@DBinary Use the official tutorials to see if you can reproduce this issue. note that you need to use the latest version of pandas, numpy and scanpy and not test in an older environment

DBinary commented 3 weeks ago

This bug has been reported here: https://github.com/owkin/PyDESeq2/pull/307

Starting from v0.10.9, anndata no longer supports pandas DataFrames or Series in varm fields. Fortunately, PyDeseq2 has addressed this bug in v0.4.11. I recommend updating your PyDeseq2 to v0.4.11 to resolve this issue.

Best wishes, Lei

DBinary commented 3 weeks ago

This bug has been fixed in the latest version of OmicVerse.