最近有一个分析任务，需要做转录因子调控网络分析，需要安装pySCENIC这个工具，颇费周折，下面是我的成功安装记录，直接拿去实践。

1.系统环境

# system

Darwin MacBook-Pro.local 24.5.0 Darwin Kernel Version 24.5.0: Tue Apr 22 19:48:46 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T8103 arm64

# conda

conda --version

conda 24.7.1

2.安装

conda create -n pyscenic python=3.8

conda activate pyscenic

conda install numpy=1.19

conda install pandas=1.3

pip install numba==0.56.4

pip install pyscenic==0.12.1

python -c "import numpy; print(numpy.__version__)"

python -c "import pandas; print(pandas.__version__)"

python -c "import pyscenic; print(pyscenic.__version__)

3.测试

pyscenic --help

zsh: correct 'pyscenic' to 'pySCENIC' [nyae]? n

OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.

usage: pyscenic [-h] {grn,add_cor,ctx,aucell} ...

Single-Cell rEgulatory Network Inference and Clustering (0.12.1)

positional arguments:

  {grn,add_cor,ctx,aucell}

                        sub-command help

    grn                Derive co-expression modules from expression matrix.

    add_cor            [Optional] Add Pearson correlations based on TF-gene expression to the network

                        adjacencies output from the GRN step, and output these to a new adjacencies

                        file. This will normally be done during the "ctx" step.

    ctx                Find enriched motifs for a gene signature and optionally prune targets from

                        this signature based on cis-regulatory cues.

    aucell              Quantify activity of gene signatures across single cells.

optional arguments:

  -h, --help            show this help message and exit

Arguments can be read from file using a @args.txt construct. For more information on loom file format

see http://loompy.org . For more information on gmt file format see

https://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Data_formats .