# Expression Skill Configuration

skill:
  name: expression
  version: "1.0.2"
  description: "Expression(FPKM/TPM)表达量绘图与RNA-seq DE自动表达图后处理"
  author: "bbav2-team"
  source: "apps/cli/run_expression.py"

input:
  expression_matrix: null  # standalone必需: FPKM/TPM表达矩阵，或由GEO下载获得
  sample_txt: null  # standalone必需: sample.txt样本分组
  gene_id_file: null  # standalone必需: 单target家族成员ID
  rnaseq_matrices: null  # rnaseq_auto可选: FPKM/TPM/VST矩阵

parameters:
  statistics:
    pvalue_threshold: 0.05
    log2fc_threshold: 1
    method: ttest  # ttest, deseq2, edgeR
    fdr_method: BH  # Benjamini-Hochberg
  visualization:
    tool: r  # r (使用rnaR环境) or python (使用rnaseq环境)
    volcano_dpi: 300
    heatmap_dpi: 300
    pca_dpi: 300
    top_genes_heatmap: 50
  filtering:
    min_count: 10   # 最小 counts
    min_samples: 2  # 最小样本数

output:
  format: ["png", "pdf", "txt"]
  report_template: "templates/report.md.j2"
  include_reproducibility: true

# conda环境配置
conda_env:
  primary: rnaR      # standalone FPKM/TPM绘图使用R环境
  fallback: rnaseq   # rnaseq_auto由RNA-seq流程触发时可用
  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"

dependencies:
  # rnaseq环境 (主环境)
  primary_conda:
    channels:
      - conda-forge
      - bioconda
    packages:
      - python=3.10
      - pandas>=2.0.0
      - numpy>=1.24.0
      - scipy>=1.10.0
      - biopython>=1.81
      - matplotlib>=3.7.0
      - seaborn>=0.12.0
      - scikit-learn>=1.3.0
  
  # rnaR环境 (备用/特定绘图)
  fallback_conda:
    channels:
      - conda-forge
      - bioconda
    packages:
      - r-base>=4.3.0
      - r-ggplot2
      - r-deseq2
      - r-edger
      - r-ggrepel
      - r-pheatmap
      - r-ggpubr
      - r-cowplot
      - r-tidyverse
  
  # 推荐安装: 合并R包到rnaseq环境
  # conda install -n rnaseq -c conda-forge -c bioconda r-ggplot2 r-deseq2 r-ggrepel r-pheatmap