Filtering scRNA-seq data

This script was used to remove poor quality transcriptomes, likely multiplets and Leishmania mexicana transcriptes and transcriptomes.

WT_01_raw_object <- CreateSeuratObject(counts = cbind(WT_01_data), project = c("WT_01"), min.cells = 5, min.features = 3)

Feature names cannot have underscores ('_'), replacing with dashes ('-')

WT_01_raw_object <- CreateSeuratObject(counts = cbind(WT_01_data), project = c("WT_01"), min.cells = 5, min.features = 3)

Feature names cannot have underscores ('_'), replacing with dashes ('-')

WT_02_raw_object <- CreateSeuratObject(counts = cbind(WT_02_data), project = c("WT_02"), min.cells = 5, min.features = 3)

Feature names cannot have underscores ('_'), replacing with dashes ('-')

WT_02_raw_object <- CreateSeuratObject(counts = cbind(WT_02_data), project = c("WT_02"), min.cells = 5, min.features = 3)

Feature names cannot have underscores ('_'), replacing with dashes ('-')

ZC3H20_raw_object <- CreateSeuratObject(counts = cbind(ZC3H20_data), project = c("ZC3H20_KO"), min.cells = 5, min.features = 3)

Feature names cannot have underscores ('_'), replacing with dashes ('-')

WT_02_raw_object <- CreateSeuratObject(counts = cbind(WT_02_data), project = c("WT_02"), min.cells = 5, min.features = 3)

Feature names cannot have underscores ('_'), replacing with dashes ('-')

ZC3H20_raw_object <- CreateSeuratObject(counts = cbind(ZC3H20_data), project = c("ZC3H20_KO"), min.cells = 5, min.features = 3)

Feature names cannot have underscores ('_'), replacing with dashes ('-')

GEM_WT_01 <- as.data.frame(gem_classification_01)
GEM_WT_01 <- subset(GEM_WT_01, select = c("call"))
GEM_WT_01 <- subset(GEM_WT_01, select = c("call"))
WT_01_raw_object <- AddMetaData(WT_01_raw_object, GEM_WT_01)
WT_01_raw_object <- AddMetaData(WT_01_raw_object, GEM_WT_01)
WT_01_raw_object_Tbrucei_subset <- subset(WT_01_raw_object, subset = call == "Tbrucei")
WT_01_raw_object_Tbrucei_subset <- subset(WT_01_raw_object, subset = call == "Tbrucei")
GEM_WT_02 <- as.data.frame(gem_classification_02)
WT_01_raw_object <- AddMetaData(WT_01_raw_object, GEM_WT_01)
WT_01_raw_object_Tbrucei_subset <- subset(WT_01_raw_object, subset = call == "Tbrucei")
GEM_WT_02 <- as.data.frame(gem_classification_02)
GEM_WT_02 <- subset(GEM_WT_02, select = c("call"))
WT_01_raw_object <- AddMetaData(WT_01_raw_object, GEM_WT_01)
WT_01_raw_object_Tbrucei_subset <- subset(WT_01_raw_object, subset = call == "Tbrucei")
GEM_WT_02 <- as.data.frame(gem_classification_02)
GEM_WT_02 <- subset(GEM_WT_02, select = c("call"))
WT_02_raw_object <- AddMetaData(WT_02_raw_object, GEM_WT_02)

WT_01 <- subset(WT_01_raw_object, subset = nFeature_RNA > 250 & nFeature_RNA < 2500 & nCount_RNA > 1000 & nCount_RNA < 4000 & percent.MT < 2 & percent.rRNA < 8)
WT_02 <- subset(WT_02_raw_object, subset = nFeature_RNA > 250 & nFeature_RNA < 2500 & nCount_RNA > 1000 & nCount_RNA < 4000 & percent.MT < 2 & percent.rRNA < 8)

ZC3H20 <- subset(ZC3H20_raw_object, subset = nFeature_RNA > 250 & nFeature_RNA < 2500 & nCount_RNA > 1000 & nCount_RNA < 4000 & percent.MT < 2 & percent.rRNA < 8)

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