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#author("2026-06-08T11:14:23+00:00","default:sysosa","sysosa") #author("2026-06-08T11:19:05+00:00","default:sysosa","sysosa") ドキュメント [[https://cellbender.readthedocs.io/en/latest/index.html>+https://cellbender.readthedocs.io/en/latest/index.html]] github [[https://github.com/broadinstitute/CellBender>+https://github.com/broadinstitute/CellBender]] pipy [[https://pypi.org/project/cellbender/>+https://pypi.org/project/cellbender/]] #code(nonumber){{ git clone https://github.com/yyuu/pyenv.git /apps/pyenv export PYENV_ROOT=/apps/pyenv export PATH=$PYENV_ROOT/bin:$PATH pyenv install miniforge3-26.3.2-1 source /apps/pyenv/versions/miniforge3-26.3.2-1/etc/profile.d/conda.sh conda update conda (既に環境があるなら) source /apps/pyenv/versions/miniforge3-26.3.2-1/etc/profile.d/conda.sh }} #code(nonumber){{ [root@r9 ~]# cat /etc/redhat-release Rocky Linux release 9.7 (Blue Onyx) [root@r9 ~]# cat /proc/driver/nvidia/version NVRM version: NVIDIA UNIX Open Kernel Module for x86_64 595.58.03 Release Build (dvs-builder@U22-I3-AM25-28-3) Tue Mar 17 19:55:10 UTC 2026 GCC version: gcc version 11.5.0 20240719 (Red Hat 11.5.0-11) (GCC) [root@r9 ~]# nvidia-smi -L GPU 0: NVIDIA RTX PRO 2000 Blackwell (UUID: GPU-40660e37-0d35-d4f4-294a-eee3fe83049e) [root@r9 ~]# }} #code(nonumber){{ [root@r9 ~]# conda create -n cellbender python=3.12 [root@r9 ~]# conda activate cellbender (cellbender) [root@r9 ~]# (cellbender) [root@r9 ~]# conda install -c anaconda pytables (cellbender) [root@r9 ~]# pip install torch (cellbender) [root@r9 ~]# conda list # packages in environment at /apps/pyenv/versions/miniforge3-26.3.2-1/envs/cellbender: # # Name Version Build Channel _openmp_mutex 4.5 20_gnu conda-forge aws-c-auth 0.10.1 h47b2149_0 anaconda aws-c-cal 0.9.13 h1b28b03_0 anaconda aws-c-common 0.12.6 h47b2149_0 anaconda aws-c-compression 0.3.2 h47b2149_0 anaconda aws-c-http 0.10.13 h47b2149_0 anaconda aws-c-io 0.26.3 h1b29dbc_0 anaconda aws-c-s3 0.12.0 h1b28b03_1 anaconda aws-c-sdkutils 0.2.4 h47b2149_2 anaconda aws-checksums 0.2.10 h47b2149_0 anaconda blas 1.0 openblas anaconda blosc 1.21.6 he440d0b_1 conda-forge bzip2 1.0.8 hda65f42_9 conda-forge c-ares 1.34.6 hd44998d_0 anaconda c-blosc2 2.22.0 hc31b594_1 conda-forge ca-certificates 2026.5.20 hbd8a1cb_0 conda-forge cuda-bindings 13.3.1 pypi_0 pypi cuda-pathfinder 1.5.5 pypi_0 pypi cuda-toolkit 13.0.2 pypi_0 pypi filelock 3.29.1 pypi_0 pypi fsspec 2026.4.0 pypi_0 pypi gettext 0.25.1 h92eb808_0 anaconda gettext-tools 0.25.1 h6a67909_0 anaconda hdf5 2.0.0 h91801a2_3 anaconda icu 78.3 h84d19a5_0 anaconda jansson 2.15.0 hbcba0ee_0 anaconda jinja2 3.1.6 pypi_0 pypi ld_impl_linux-64 2.45.1 default_hbd61a6d_102 conda-forge libasprintf 0.25.1 hf2ab22a_0 anaconda libasprintf-devel 0.25.1 hf2ab22a_0 anaconda libbrotlicommon 1.2.0 h32cd6e7_0 anaconda libbrotlidec 1.2.0 ha2c5f68_0 anaconda libbrotlienc 1.2.0 h2e96acb_0 anaconda libcurl 8.20.0 hd8fa685_1 anaconda libev 4.33 h7f8727e_1 anaconda libexpat 2.8.1 hecca717_0 conda-forge libffi 3.5.2 h3435931_0 conda-forge libgcc 15.2.0 he0feb66_19 conda-forge libgcc-ng 15.2.0 h69a702a_19 conda-forge libgettextpo 0.25.1 hf2ab22a_0 anaconda libgettextpo-devel 0.25.1 hf2ab22a_0 anaconda libgfortran 15.2.0 h166f726_7 anaconda libgfortran5 15.2.0 hc633d37_7 anaconda libgomp 15.2.0 he0feb66_19 conda-forge libiconv 1.18 h75a1612_0 anaconda libidn2 2.3.8 hf80d704_0 anaconda libkrb5 1.22.1 h869c75e_1 anaconda liblzma 5.8.3 hb03c661_0 conda-forge liblzma-devel 5.8.3 hb03c661_0 conda-forge libnghttp2 1.69.0 hc59f8b6_0 anaconda libnsl 2.0.1 hb9d3cd8_1 conda-forge libopenblas 0.3.31 hf7dbefb_2 anaconda libsqlite 3.53.2 h0c1763c_0 conda-forge libssh2 1.11.1 hcf80075_0 conda-forge libstdcxx 15.2.0 h934c35e_19 conda-forge libstdcxx-ng 15.2.0 hdf11a46_19 conda-forge libunistring 1.4.2 h34b0ebb_0 anaconda libuuid 2.42.1 h5347b49_0 conda-forge libxcrypt 4.4.36 hd590300_1 conda-forge libxml2 2.14.6 hf2a51f9_1 anaconda libzlib 1.3.2 h25fd6f3_2 conda-forge lmdb 0.9.31 hb25bd0a_0 anaconda lz4-c 1.10.0 h5888daf_1 conda-forge lzo 2.10 h7b6447c_2 anaconda markupsafe 3.0.3 pypi_0 pypi mpmath 1.3.0 pypi_0 pypi ncurses 6.6 hdb14827_0 conda-forge networkx 3.6.1 pypi_0 pypi numexpr 2.14.1 py312h5c6250f_1 anaconda numpy 2.4.6 py312h35deafb_0 anaconda numpy-base 2.4.6 py312h4bc27c9_0 anaconda nvidia-cublas 13.1.1.3 pypi_0 pypi nvidia-cuda-cupti 13.0.85 pypi_0 pypi nvidia-cuda-nvrtc 13.0.88 pypi_0 pypi nvidia-cuda-runtime 13.0.96 pypi_0 pypi nvidia-cudnn-cu13 9.20.0.48 pypi_0 pypi nvidia-cufft 12.0.0.61 pypi_0 pypi nvidia-cufile 1.15.1.6 pypi_0 pypi nvidia-curand 10.4.0.35 pypi_0 pypi nvidia-cusolver 12.0.4.66 pypi_0 pypi nvidia-cusparse 12.6.3.3 pypi_0 pypi nvidia-cusparselt-cu13 0.8.1 pypi_0 pypi nvidia-nccl-cu13 2.29.7 pypi_0 pypi nvidia-nvjitlink 13.0.88 pypi_0 pypi nvidia-nvshmem-cu13 3.4.5 pypi_0 pypi nvidia-nvtx 13.0.85 pypi_0 pypi openssl 3.6.2 h35e630c_0 conda-forge packaging 26.2 pyhc364b38_0 conda-forge pip 26.1.2 pyh8b19718_0 conda-forge py-cpuinfo 9.0.0 py312h06a4308_0 anaconda pytables 3.11.1 py312h4db2897_0 anaconda python 3.12.13 hd63d673_0_cpython conda-forge readline 8.3 h853b02a_0 conda-forge s2n 1.6.2 h02aa81b_0 anaconda setuptools 81.0.0 pypi_0 pypi snappy 1.2.1 h6a678d5_0 anaconda sympy 1.14.0 pypi_0 pypi tk 8.6.13 noxft_h366c992_103 conda-forge torch 2.12.0 pypi_0 pypi triton 3.7.0 pypi_0 pypi typing-extensions 4.15.0 py312h06a4308_0 anaconda typing_extensions 4.15.0 py312h06a4308_0 anaconda tzdata 2025c hc9c84f9_1 conda-forge wheel 0.47.0 pyhd8ed1ab_0 conda-forge xz 5.8.3 ha02ee65_0 conda-forge xz-gpl-tools 5.8.3 ha02ee65_0 conda-forge xz-tools 5.8.3 hb03c661_0 conda-forge zlib 1.3.2 h25fd6f3_2 conda-forge zlib-ng 2.3.3 hcff5ade_0 anaconda zstd 1.5.7 hb78ec9c_6 conda-forge (cellbender) [root@r9 ~]# }} #code(nonumber){{ (cellbender) [root@r9 ~]# python Python 3.12.13 | packaged by conda-forge | (main, Mar 5 2026, 16:50:00) [GCC 14.3.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import torch >>> print(torch.cuda.is_available()) True >>> print(torch.cuda.get_device_name()) NVIDIA RTX PRO 2000 Blackwell >>> quit(); (cellbender) [root@r9 ~]# }} #code(nonumber){{ (cellbender) [root@r9 ~]# cd /apps (cellbender) [root@r9 apps]# git clone https://github.com/broadinstitute/CellBender.git (cellbender) [root@r9 apps]# pip install -e CellBender (cellbender) [root@r9 apps]# conda deactivate [root@r9 ~]# }} 「/apps/modulefiles/CellBender」 #code(nonumber){{ #%Module set root /apps/pyenv/versions/miniforge3-26.3.2-1/envs/cellbender prepend-path PATH $root/bin prepend-path LD_LIBRARY_PATH $root/lib }} #code(nonumber){{ [saber@r9 ~]$ module load CellBender [saber@r9 ~]$ mkdir test [saber@r9 ~]$ cd test/ [saber@r9 test]$ git clone https://github.com/broadinstitute/CellBender [saber@r9 test]$ cd CellBender/ [saber@r9 CellBender]$ [saber@r9 CellBender]$ cd examples/remove_background/ [saber@r9 remove_background]$ python generate_tiny_10x_dataset.py Downloading heart10k (CellRanger 3.0.0, v3 Chemistry)... --2026-06-08 20:15:30-- https://cf.10xgenomics.com/samples/cell-exp/3.0.0/heart_10k_v3/heart_10k_v3_raw_feature_bc_matrix.h5 Resolving cf.10xgenomics.com (cf.10xgenomics.com)... 104.18.1.173, 104.18.0.173, 2606:4700::6812:1ad, ... Connecting to cf.10xgenomics.com (cf.10xgenomics.com)|104.18.1.173|:443... connected. HTTP request sent, awaiting response... 200 OK Length: 167177525 (159M) [binary/octet-stream] Saving to: ‘heart10k_raw_feature_bc_matrix.h5’ heart10k_raw_feature_bc_matrix.h5 100%[==========================================================================>] 159.43M 32.0MB/s in 5.7s 2026-06-08 20:15:37 (28.0 MB/s) - ‘heart10k_raw_feature_bc_matrix.h5’ saved [167177525/167177525] Loading the dataset... /apps/pyenv/versions/miniforge3-26.3.2-1/envs/cellbender/lib/python3.12/site-packages/legacy_api_wrap/__init__.py:88: FutureWarning: The dtype argument is deprecated and will be removed in late 2024. return fn(*args_all, **kw) Raw dataset size (6794880, 31053) Trimming heart10k (CellRanger 3.0.0, v3 Chemistry)... Number of genes in the trimmed dataset: 100 Number of barcodes in the trimmed dataset: 37760 Expected number of cells in the trimmed dataset: 500 AnnData object with n_obs × n_vars = 37760 × 100 var: 'gene_id', 'genome', 'feature_type' uns: 'cellranger_version' Saving the trimmed dataset as tiny_raw_feature_bc_matrix.h5ad ... Done! [saber@r9 remove_background]$ [saber@r9 remove_background]$ cellbender remove-background \ --input tiny_raw_feature_bc_matrix.h5ad \ --output tiny_output.h5 \ --expected-cells 500 \ --total-droplets-included 2000 \ --cuda : : [saber@r9 remove_background]$ ls -lrt total 205908 -rw-r--r-- 1 saber saber 167177525 Nov 15 2018 heart10k_raw_feature_bc_matrix.h5 -rwxr-xr-x 1 saber saber 3058 Jun 8 20:07 generate_tiny_10x_dataset.py -rw-r--r-- 1 saber saber 14660728 Jun 8 20:15 tiny_raw_feature_bc_matrix.h5ad -rw-r--r-- 1 saber saber 2134377 Jun 8 20:17 tiny_output_posterior.h5 -rw-r--r-- 1 saber saber 24664467 Jun 8 20:17 ckpt.tar.gz -rw-r--r-- 1 saber saber 118891 Jun 8 20:17 tiny_output.pdf -rw-r--r-- 1 saber saber 12369 Jun 8 20:17 tiny_output_cell_barcodes.csv -rw-r--r-- 1 saber saber 940820 Jun 8 20:17 tiny_output.h5 -rw-r--r-- 1 saber saber 351137 Jun 8 20:17 tiny_output_filtered.h5 -rw-r--r-- 1 saber saber 573 Jun 8 20:17 tiny_output_metrics.csv -rw-r--r-- 1 saber saber 740831 Jun 8 20:17 tiny_output_report.html -rw-r--r-- 1 saber saber 18246 Jun 8 20:17 tiny_output.log [saber@r9 remove_background]$ }}
