Limma批量效应校正后的负值

Question

我有几个RNA-seq数据集。采用反褶积方法，对每一组数据进行了细胞型富集分析，并将结果合并为一组数据，得到列中的1000+样本和行中的38个单元类型。这些数据集来自不同的癌症文章。因此，在使用火山图或the可视化数据之前，我需要纠正癌症类型和数据集的批处理效应，这样源就不会影响结果。我这样做是使用以下代码：

scores.batch = limma::removeBatchEffect(scores ,metadata$Cancer_Type, metadata$dataset)

然而，对于一些样本中的一些单元格类型，我得到了一个负值，这当然没有意义。有些地方不对劲。

得分矩阵的dput：

structure(c(0, 0.0853672252935787, 0.0472255148477786, 0.0505467828272972, 
0, 0.0308325695761715, 0, 0.157955518619051, 0.00989687292281167, 
0.03263377453636, 0.174135667551838, 0.0287360256296349, 0.0647519562755579, 
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0.220714394591806, 0.0357916262655448, 0.0545063692410225, 0, 
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0.0264858410661633, 0, 0.00902616117758849, 0.10613905468228, 
0, 0, 0.0868373941926339), .Dim = c(20L, 20L), .Dimnames = list(
    c("Adipocytes", "B-cells", "Basophils", "CD4+ memory T-cells", 
    "CD4+ naive T-cells", "CD4+ T-cells", "CD4+ Tcm", "CD4+ Tem", 
    "CD8+ naive T-cells", "CD8+ T-cells", "CD8+ Tcm", "Class-switched memory B-cells", 
    "DC", "Endothelial cells", "Eosinophils", "Epithelial cells", 
    "Fibroblasts", "Hepatocytes", "ly Endothelial cells", "Macrophages"
    ), c("Pt1", "Pt10", "Pt103", "Pt106", "Pt11", "Pt17", "Pt2", 
    "Pt24", "Pt26", "Pt27", "Pt28", "Pt29", "Pt31", "Pt36", "Pt37", 
    "Pt38", "Pt39", "Pt4", "Pt46", "Pt47")))

我又累了，只为Cancer_Type校正，但结果并不好( the没有按我的需要对数据进行聚类)。

这里可能有什么问题？

Answer 1

Limma假设这两种类型的批处理效应都是加性的，因此是独立的。编写limma::removeBatchEffect(x = scores, batch = cancer_type, batch2 = study意味着癌症类型与研究数据集之间没有关系。然而，很可能一项研究是关于一种癌症类型，另一项研究是关于另一种癌症类型。因此，边界模型破裂的假设很可能被打破。

但是，您可以只创建一个批处理，并将其用作单个批处理参数：

metadata$merged_batch <- paste0(metadata$Cancer_Type, metadata$dataset)

scores.batch = limma::removeBatchEffect(scores, batch = metadata$merged_batch)