bio-de-results

npx skills add majiayu000/claude-skill-registry --skill de-results-gptomics-bioskills-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# DE Results Extract, filter, and export differential expression results. ## Required Libraries ```r library(DESeq2) # or library(edgeR) library(dplyr) # For data manipulation ``` ## Extracting DESeq2 Results ```r # Basic results res <- results(dds) # With specific alpha (adjusted p-value threshold) res <- results(dds, alpha = 0.05) # With log fold change shrinkage res <- lfcShrink(dds, coef = 'condition_treated_vs_control', type = 'apeglm') # Convert to data frame res_df <- as.data.frame(res) res_df$gene <- rownames(res_df) ``` ## Extracting edgeR Results ```r # Get all results results <- topTags(qlf, n = Inf)$table # Add gene column results$gene <- rownames(results) ``` ## Filtering Significant Genes ### By Adjusted P-value ```r # DESeq2 sig_genes <- subset(res, padj < 0.05) # edgeR sig_genes <- subset(results, FDR < 0.05) # Using dplyr sig_genes <- res_df %>% filter(padj < 0.05) %>% arrange(padj) ``` ### By Fold Change ```r # Absolute log2 fold change > 1 (2-fold change) sig_genes <- subset(res, padj < 0.05 & abs(log2FoldChange) > 1) # Up-regulated only up_genes <- subset(res, padj < 0.05 & log2FoldChange > 1) # Down-regulated only down_genes <- subset(res, padj < 0.05 & log2Fol