76 lines
2.0 KiB
YAML
Executable File
76 lines
2.0 KiB
YAML
Executable File
# Expression Skill Configuration
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skill:
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name: expression
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version: "1.0.2"
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description: "Expression(FPKM/TPM)表达量绘图与RNA-seq DE自动表达图后处理"
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author: "bbav2-team"
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source: "apps/cli/run_expression.py"
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input:
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expression_matrix: null # standalone必需: FPKM/TPM表达矩阵，或由GEO下载获得
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sample_txt: null # standalone必需: sample.txt样本分组
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gene_id_file: null # standalone必需: 单target家族成员ID
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rnaseq_matrices: null # rnaseq_auto可选: FPKM/TPM/VST矩阵
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parameters:
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statistics:
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pvalue_threshold: 0.05
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log2fc_threshold: 1
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method: ttest # ttest, deseq2, edgeR
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fdr_method: BH # Benjamini-Hochberg
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visualization:
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tool: r # r (使用rnaR环境) or python (使用rnaseq环境)
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volcano_dpi: 300
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heatmap_dpi: 300
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pca_dpi: 300
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top_genes_heatmap: 50
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filtering:
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min_count: 10 # 最小 counts
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min_samples: 2 # 最小样本数
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output:
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format: ["png", "pdf", "txt"]
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report_template: "templates/report.md.j2"
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include_reproducibility: true
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# conda环境配置
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conda_env:
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primary: rnaR # standalone FPKM/TPM绘图使用R环境
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fallback: rnaseq # rnaseq_auto由RNA-seq流程触发时可用
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note: "Expression阶段不是DESeq2差异分析；rnaseq_de负责差异表达，expression负责表达量图"
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dependencies:
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# rnaseq环境 (主环境)
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primary_conda:
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channels:
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- conda-forge
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- bioconda
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packages:
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- python=3.10
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- pandas>=2.0.0
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- numpy>=1.24.0
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- scipy>=1.10.0
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- biopython>=1.81
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- matplotlib>=3.7.0
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- seaborn>=0.12.0
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- scikit-learn>=1.3.0
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# rnaR环境 (备用/特定绘图)
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fallback_conda:
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channels:
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- conda-forge
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- bioconda
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packages:
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- r-base>=4.3.0
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- r-ggplot2
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- r-deseq2
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- r-edger
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- r-ggrepel
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- r-pheatmap
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- r-ggpubr
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- r-cowplot
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- r-tidyverse
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# 推荐安装: 合并R包到rnaseq环境
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# conda install -n rnaseq -c conda-forge -c bioconda r-ggplot2 r-deseq2 r-ggrepel r-pheatmap |