我试图在seurat对象上运行DoubletFinder,这是由于集成了各种数据集。
Seurat对象有两个测试: RNA和整合。
完整的seurat对象已被完全处理:
paramSweep_v3()函数的DoubletFinder提供了以下输出:
sweep.res.list <- paramSweep_v3(integrated.seu, PCs = 1:38, sct = FALSE)
Loading required package: fields
Loading required package: spam
Loading required package: dotCall64
Loading required package: grid
Spam version 2.5-1 (2019-12-12) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.
Attaching package: ‘spam’
The following object is masked from ‘package:R.utils’:
cleanup
The following objects are masked from ‘package:base’:
backsolve, forwardsolve
Loading required package: maps
See https://github.com/NCAR/Fields for
an extensive vignette, other supplements and source code
[1] "Creating artificial doublets for pN = 5%"
[1] "Creating Seurat object..."
[1] "Normalizing Seurat object..."
Error in NormalizeData.default(object = GetAssayData(object = object, :
trying to get slot "params" from an object of a basic class ("NULL") with no slots
为什么这表明我的Seurat对象中没有插槽?
发布于 2020-06-18 19:11:35
DoubletFinder自述文件清楚地指出,不应该在聚合数据集中运行它。它将产生假的人工双打:
[https://github.com/chris-mcginnis-ucsf/DoubletFinder][1]
不将DoubletFinder应用于代表多个不同样本(例如,多个10X通道)的聚集scRNA-seq数据。例如,如果您在代表WT和跨不同10X通道排序的突变细胞系的聚合数据上运行DoubletFinder,则将从WT和变种人单元中生成人工双值,而这些细胞并不存在于您的数据中。这些人工的双打会扭曲结果。值得注意的是,通过在多个10X通道上分割单个样本生成的数据运行DoubletFinder是可以的。
我这样做的方法是阅读各个示例,分别对它们进行聚类,运行DoubletFinder,删除双元素,然后运行集成工作流。
https://stackoverflow.com/questions/62266462
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