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105 lines
2.9 KiB
105 lines
2.9 KiB
library(tidyverse)
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library(flowWorkspace)
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library(Biobase)
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library(flowGate)
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source("functionsCyto.R")
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files<-list.files("Files", pattern = ".LMD", full.names = T)
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LMD2FCS(files)
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fs<-read.ncdfFlowSet(files=list.files("Files",".fcs", full.names = T), readonly = F)
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gs <- GatingSet(fs)
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comp<-as.matrix(read.csv("CompMatrix.csv", check.names = F, row.names = 1))
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gs<-compensate(gs, comp)
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trans_params<-transform_gs(gs)
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saveRDS(trans_params, "trans_params.rds")
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trans_params<-readRDS("trans_params.rds")
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trans_apply(gs, trans_params = trans_params)
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colnames(gs)[c(4,6,11)]<-c("CD16","CD56","CD107a")
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sampleNames(gs)<-gsub("\\s[0-9]*.fcs","",sampleNames(gs))
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sampleNames(gs)<-gsub(".*\\s","",sampleNames(gs))
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pData(gs)$name<-rownames(pData(gs))
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gates<-list()
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gs_gate_interactive(gs,
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filterId = "Leukocytes",
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dims = list("FS-A", "SS-A"))
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gates[["Leukocytes"]]<-gs_pop_get_gate(gs, "Leukocytes")
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gs_gate_interactive(gs,
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subset = "Leukocytes",
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filterId = "NKdim",
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dims = list("CD16", "CD56"))
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gates[["NKdim"]]<-gs_pop_get_gate(gs, "NKdim")
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gs_gate_interactive(gs[["NKs-K562"]],
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subset = "NKdim",
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filterId = "CD107a+",
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dims = list("CD107a", "CD56"))
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gates[["CD107a+"]]<-gs_pop_get_gate(gs, "CD107a+")
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gates<-gates_save(gs, file = "gates.rds")
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gates<-readRDS("gates.rds")
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gs<-gates_apply(gs, gates)
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autoplot(gs, "CD107a+")
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ggcyto_trans(gs, "CD107a", "CD56", subset="NKdim")
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autoplot(gs[[5]], bins=0)
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ggcyto_trans_all(gs, index = 5, ncol=1)
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stats<-gs_pop_get_stats(gs, nodes="CD107a+", type="perc")
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ggpubr::ggarrange(
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ggcyto_trans_all(gs, nrow=1),
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ggcyto::as.ggplot(ggcyto_trans(gs, "CD107a", "CD56", subset="NKdim")+
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facet_grid(.~name)),
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ggplot(stats, aes(sample, percent))+
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geom_bar(stat="identity", color="black", fill="grey70"),
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ncol=1)
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ggsave("Analysis.jpg")
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save_gs(gs, "gs_analysis")
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gs<-load_gs("gs_analysis/")
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## For a new experiment with same settings
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files<-list.files("Files", pattern = ".LMD", full.names = T)
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LMD2FCS(files)
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fs<-read.ncdfFlowSet(files=list.files("Files",".fcs", full.names = T), readonly = F)
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gs <- GatingSet(fs)
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comp<-as.matrix(read.csv("CompMatrix.csv", check.names = F, row.names = 1))
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gs<-compensate(gs, comp)
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trans_params<-readRDS("trans_params.rds")
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trans_apply(gs, trans_params = trans_params)
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colnames(gs)[c(4,6,11)]<-c("CD16","CD56","CD107a")
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sampleNames(gs)<-gsub("\\s[0-9]*.fcs","",sampleNames(gs))
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sampleNames(gs)<-gsub(".*\\s","",sampleNames(gs))
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pData(gs)$name<-rownames(pData(gs))
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gates<-readRDS("gates.rds")
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gs<-gates_apply(gs, gates) #if not the same gates, apply a general with "exact=F"
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stats<-gs_pop_get_stats(gs, nodes="CD107a+", type="perc")
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ggpubr::ggarrange(
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ggcyto_trans_all(gs, nrow=1),
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ggcyto::as.ggplot(ggcyto_trans(gs, "CD107a", "CD56", subset="NKdim")+
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facet_grid(.~name)),
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ggplot(stats, aes(sample, percent))+
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geom_bar(stat="identity", color="black", fill="grey70"),
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ncol=1)
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ggsave("Analysis.jpg")
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save_gs(gs, "gs_analysis")
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gs<-load_gs("gs_analysis/")
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