In satijalab/seurat-wrappers: Community-Provided Methods and Extensions for the Seurat Object

This vigettte demonstrates the use of the Harmony package in Seurat. Commands and parameters are based off of the Harmony use page. If you use Harmony in your work, please cite:

Fast, sensitive, and flexible integration of single cell data with Harmony

Ilya Korsunsky, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, Michael Brenner, Po-Ru Loh, Soumya Raychaudhuri

bioRxiv, 2019

doi: 10.1101/461954v2

GitHub: https://github.com/immunogenomics/harmony

knitr::opts_chunk$set(
  tidy = TRUE,
  tidy.opts = list(width.cutoff = 95),
  message = FALSE,
  warning = FALSE
)

Prerequisites to install:

• Seurat
• Harmony
• SeuratData

Note that SeuratWrappers is not necessary, as the wrapper functions were generously provided by the Harmony authors, and are included when installing Harmony.

library(harmony)
library(Seurat)
library(SeuratData)

{.tabset .tabset-pills}

Systematic comparative analysis of human PBMC

To learn more about this dataset, type ?pbmcsca

InstallData("pbmcsca")
data("pbmcsca")
pbmcsca <- NormalizeData(pbmcsca) %>% FindVariableFeatures() %>% ScaleData() %>% RunPCA(verbose = FALSE)
pbmcsca <- RunHarmony(pbmcsca, group.by.vars = 'Method')
pbmcsca <- RunUMAP(pbmcsca, reduction = 'harmony', dims = 1:30)
pbmcsca <- FindNeighbors(pbmcsca, reduction = 'harmony', dims = 1:30) %>% FindClusters()
DimPlot(pbmcsca, group.by = c('Method', 'ident',"CellType"), ncol = 3)

Interferon-stimulated and control PBMC

To learn more about this dataset, type ?ifnb

InstallData("ifnb")
data("ifnb")
ifnb <- NormalizeData(ifnb) %>% FindVariableFeatures() %>% ScaleData() %>% RunPCA(verbose = FALSE)
ifnb <- RunHarmony(ifnb, group.by.vars = 'stim')
ifnb <- RunUMAP(ifnb, reduction = 'harmony', dims = 1:30)
ifnb <- FindNeighbors(ifnb, reduction = 'harmony', dims = 1:30) %>% FindClusters()
DimPlot(ifnb, group.by = c("stim", "ident", "seurat_annotations"), ncol = 3)

Eight human pancreatic islet datasets

To learn more about this dataset, type ?panc8

InstallData("panc8")
data("panc8")
panc8 <- NormalizeData(panc8) %>% FindVariableFeatures() %>% ScaleData() %>% RunPCA(verbose = FALSE)
panc8 <- RunHarmony(panc8, group.by.vars = 'replicate')
panc8 <- RunUMAP(panc8, reduction = 'harmony', dims = 1:30)
panc8 <- FindNeighbors(panc8, reduction = 'harmony', dims = 1:30) %>% FindClusters()
DimPlot(panc8, group.by = c("replicate", "ident","celltype"), ncol = 3)

satijalab/seurat-wrappers documentation built on April 10, 2024, 3:25 p.m.