一文搞定高通量数据整合分析中批次效应的鉴定和处理

2024年2月4日发(作者：)

head(expr_mat_batch_correct_limma3)## untrt_N61311 untrt_N052611 untrt_N080611 untrt_N061011 trt_N61311 trt_N052611## ENSG 4.994311 4.994311 4.994311 4.994311 9.018199 9.018199## ENSG 7.015663 7.015663 7.015663 7.015663 10.529444 10.529444## ENSG 6.315493 6.315493 6.315493 6.315493 6.323813 6.323813## ENSG 8.535034 8.535034 8.535034 8.535034 12.067849 12.067849## ENSG 7.152546 7.152546 7.152546 7.152546 7.309725 7.309725## ENSG 8.722104 8.722104 8.722104 8.722104 11.337083 11.337083## trt_N080611 trt_N061011## ENSG 9.018199 9.018199## ENSG 10.529444 10.529444## ENSG 6.323813 6.323813## ENSG 12.067849 12.067849## ENSG 7.309725 7.309725## ENSG 11.337083 11.337083untrt_down_genes <- "Name;TypeENSG;SVA_batch_specificENSG;SVA_batch_uncorrect_commonENSG;Uncorrect_specificENSG;Known_batch_uncorrect_commonENSG;Known_batch_specificENSG;Known_batch_SVA_batch_commonENSG;All_common"untrt_down_genes <- (text=untrt_down_genes, sep=";", header=T, =NULL)untrt_down_genes_expr <- merge(untrt_down_genes, expr_mat_batch_correct, by.x="Name", by.y=0, all.x=T)untrt_down_genes_expr_long <- reshape2::melt(untrt_down_genes_expr, id_vars=c("Name","Type"), ="Sample", = "Expr")head(untrt_down_genes_expr_long)## Name Type Sample Expr## 1 ENSG Uncorrect_specific untrt_N61311 8.902048## 2 ENSG SVA_batch_specific untrt_N61311 6.218603## 3 ENSG Known_batch_uncorrect_common untrt_N61311 9.411138## 4 ENSG All_common untrt_N61311 7.002840## 5 ENSG Known_batch_specific untrt_N61311 7.752616## 6 ENSG SVA_batch_uncorrect_common untrt_N61311 12.512617metadata$Sample = rownames(metadata)sp_boxplot(untrt_down_genes_expr_long, melted=T, metadata=metadata, xvariable = "conditions", yvariable = "Expr", jitter_bp = T, group_variable_for_line = "individual", facet_variable = "Type", facet_scales="free_y", on = c(0.7,0.1), x_label="",manual_color_vector = "Set2") + theme(ion = "horizontal")

untrt_down_genes <- "Name;TypeENSG;SVA_batch_specificENSG;SVA_batch_uncorrect_commonENSG;Uncorrect_specificENSG;Known_batch_uncorrect_commonENSG;Known_batch_specificENSG;Known_batch_SVA_batch_commonENSG;All_common"untrt_down_genes <- (text=untrt_down_genes, sep=";", header=T, =NULL)untrt_down_genes_expr <- merge(untrt_down_genes, expr_mat_batch_correct_limma1, by.x="Name", by.y=0, all.x=T)untrt_down_genes_expr_long <- reshape2::melt(untrt_down_genes_expr, id_vars=c("Name","Type"), ="Sample", = "Expr")head(untrt_down_genes_expr_long)## Name Type Sample Expr## 1 ENSG Uncorrect_specific untrt_N61311 8.918012## 2 ENSG SVA_batch_specific untrt_N61311 6.144405## 3 ENSG Known_batch_uncorrect_common untrt_N61311 9.463196## 4 ENSG All_common untrt_N61311 6.994996## 5 ENSG Known_batch_specific untrt_N61311 7.874258## 6 ENSG SVA_batch_uncorrect_common untrt_N61311 12.453728metadata$Sample = rownames(metadata)sp_boxplot(untrt_down_genes_expr_long, melted=T, metadata=metadata, xvariable = "conditions", yvariable = "Expr", jitter_bp = T, group_variable_for_line = "individual", facet_variable = "Type", facet_scales="free_y", on = c(0.7,0.1), x_label="",manual_color_vector = "Set2") + theme(ion = "horizontal")