bio-chipseq-visualization:可视化 ChIP-seq data ,使用 deepTools,Gviz,、 ChIPseeker。 创建 heatmaps,profile plots,、 genome browser…
数据与复现
BI
bio-data-visualization-volcano-customization
维护者 FreedomIntelligence · 最近更新 2026年4月1日
bio-data-visualization-volcano-customization:Customized volcano plots ,支持 ggplot2 或 matplotlib ,用于 DE results。
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-data-visualization-volcano-customization
- 维护者
- FreedomIntelligence
- 许可
- MIT
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- df$significance <- case_when( df$padj < 0.05 & df$log2FoldChange > 1 ~ 'Up',df$padj < 0.05 & df$log2FoldChange < -1 ~ 'Down',TRUE ~ 'NS' )。
- ggplot(df,aes(x = log2FoldChange,y = -log10(pvalue))) + geom_point(aes(color = significance),alpha = 0.6,size = 1.5) + scale_color_manual(values = c(Up = '#E64B35',Down = '#4DBBD5',NS = 'gray70')) + geom_hline(yintercept = -log10(0.05),linetype = 'dashed',color = 'gray40') + geom_vline(xintercept = c(-1,1),linetype = 'dashed',color = 'gray40') + theme_classic() + labs(x = 'log2 Fold Change',y = '-log10(p-value)',color = 'Regulation')。
- top_genes <- df %>% filter(padj < 0.05,abs(log2FoldChange) > 1) %>% arrange(pvalue) %>% head(20)。
- ggplot(df,aes(x = log2FoldChange,y = -log10(pvalue))) + geom_point(aes(color = significance),alpha = 0.6,size = 1.5) + scale_color_manual(values = c(Up = '#E64B35',Down = '#4DBBD5',NS = 'gray70')) + geom_text_repel( data = top_genes,aes(label = gene),size = 3,max.overlaps = 20,box.padding = 0.5,segment.color = 'gray50' ) + theme_classic()。
原始文档
SKILL.md 摘录
ggplot2 Basic Volcano
library(ggplot2)
library(ggrepel)
## Label specific genes of interest
genes_of_interest <- c('TP53', 'BRCA1', 'MYC', 'EGFR')
highlight_df <- df %>% filter(gene %in% genes_of_interest)
ggplot(df, aes(x = log2FoldChange, y = -log10(pvalue))) +
geom_point(aes(color = significance), alpha = 0.4, size = 1.5) +
geom_point(data = highlight_df, color = 'black', size = 3) +
geom_text_repel(data = highlight_df, aes(label = gene), fontface = 'bold') +
theme_classic()
EnhancedVolcano (R)
library(EnhancedVolcano)
适用场景
- Use bio-data-visualization-volcano-customization to prepare 论文级图表。
- Apply bio-data-visualization-volcano-customization when results need clear visual communication。
不适用场景
- Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。
上游相关技能
- differential-expression/de-visualization - DE-specific plots
- data-visualization/ggplot2-fundamentals - General ggplot2
- data-visualization/color-palettes - Color selection
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