Files
2026-08-03 18:42:47 +08:00

76 lines
2.0 KiB
YAML
Executable File

# 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