Hello,
I am currently working with multiple replicates for 2 different conditions (stimulated and unstimulated cells) that I want to integrate to adjust to correct for batch effects.
I was wondering, if there is a way (or parameter), which can be adjusted to control the integration strength or stringency. I am afraid that cell types that are unique to the stimulated condition, are projected onto the "wrong" cells, because the integration is to stringent, so I want to try out different settings.
Any help is much appreciated.
Cheers!
(I also asked this question on the github issue page of seurat)
1 answer
You need to clarify which type of integration you are performing (rPCA or CCA?).
If it is rPCA, you can tweak the k.anchor argument.
The seurat documentation has a section dedicated exactly to that: Modifying the strength of integration.
Log in to answer this question.
-
What's the point of integrating single cell data of different conditions?
written by ARP •
-
When to use integration with scRNASeq
written by Varun Gupta
-
Analysing CITE-seq data where only 4 samples are CITE-seq and rest 11 are scRNA-seq
written by Sagrika •
-
Subsetting and merging back Seurat Object brings different results
written by Nona •
-
JoinLayers to find markers in merged or integrated analysis in seurat
written by mohammedtoufiq91
-
Subclustering of intergated cells from scRNA-seq data
written by fifty_fifty •
-
Merge or Integrate Non-Overlapping Datasets - Different Experiments and Cell Types
written by kebl4660 •
-
Forum: Correct method of Merging/Integrating multiple single cell dataset using Seurat
written by rohitsatyam102
-
Editing Hash.ID in a Seurat Object
written by roberts •
-
What's best way to perform sub-clustering in seurat integrate pipeline?
written by 623202215 •
