Dear all fellows,

What is the standard way for reproducible Seurat clustering in single cell? I have been trying to use set.seed function like

library(tidyverse)
library(Seurat)
library(patchwork)
set.seed(198752)

However, once it comes to running the following script, I get new shape of cluster all the time I rerun it. How to make it reproducible because I am planning to use it for publication.

All_arthritis_integration_UMAP<- RunHarmony(All_arthritis_normal, group.by.vars = "orig.ident")
All_arthritis_integration_UMAP <- FindNeighbors(All_arthritis_integration_UMAP, reduction= "harmony", dims = 1:40)
All_arthritis_integration_UMAP <- FindClusters(All_arthritis_integration_UMAP, resolution = 0.2)
All_arthritis_integration_UMAP <- RunUMAP(All_arthritis_integration_UMAP, reduction = "harmony", dims = 1:40,
                                   n.neighbors = 30, min.dist = 0.4, spread =3)
`

Also, I would like to ask whether I could adjust some parameters in RunUmap to make cluster look better by trying some parameters like n.neighbors= XX, min.dist= XX, spread= XXX because if I run the default function, the clusters in my data looks messy.

Kind Regards,
Synat