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Fly_age_logFC_analysis.R
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Fly_age_logFC_analysis.R
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rm(list=ls())
library(plyr)
library(tidyverse)
library(readxl)
library(limma)
getwd()
setwd("C:/Users/Connor Beveridge/Box/connor_beveridge/New/age_flies/")
# lipid_types <- c( "TAG1" = "TAG1", "TAG2" = "TAG2")
lipid_types <- c( "FFA" = "FFA","AC"="AC",
"CE"="CE","CER"="CER","PCandSM"="PCandSM","PG"="PG","PE"="PE","PI"="PI", "TAG1" = "TAG1", "TAG2" = "TAG2") #Need to add PS#,"PS"="PS")
PCA_names_to_parse <- c('5DN1','5DN2','5DN3','5DN4',"5DN5",
'5GFP1','5GFP2','5GFP3','5GFP4',"5GFP5",
'7C1','7C2','7C3','7C4',"7C5",
'7E1','7E2','7E3','7E4',"7E5",
'42C1','42C2','42C3','42C4',"42C5", ##These are controls compare C to E
'42E1','42E2','42E3','42E4',"42E5",
'40DN1','40DN2','40DN3','40DN4',"40DN5",
'40GFP1','40GFP2','40GFP3','40GFP4',"40GFP5",'40DP1','40DP2','40DP3','40DP4',"40DP5",
"SolventBlank1")
####No Neurons
PCA_names_to_parse_No_Neurons <- c('5GFP1','5GFP2','5GFP3','5GFP4',"5GFP5",
'7C1','7C2','7C3','7C4',"7C5",
'7E1','7E2','7E3','7E4',"7E5",
'42C1','42C2','42C3','42C4',"42C5", ##These are controls compare C to E
'42E1','42E2','42E3','42E4',"42E5",
'40GFP1','40GFP2','40GFP3','40GFP4',"40GFP5",'40DP1','40DP2','40DP3','40DP4',"40DP5",
"SolventBlank1")
# PCA_names_to_parse <- c('5DN1','5DN2','5DN3','5DN4',"5DN5",
# '5GFP1','5GFP2','5GFP3','5GFP4',"5GFP5",
# '7C1','7C2','7C3','7C4',"7C5",
# '40C1','40C2','40C3','40C4',"40C5", ##These are controls compare C to E
# '40DN1','40DN2','40DN3','40DN4',"40DN5",
# '40DP1','40DP2','40DP3','40DP4',"40DP5",
# '40GFP1','40GFP2','40GFP3','40GFP4',"40GFP5",
# "SolventBlank1")
###5 vs 40 N
experiment_1_names <- c('40DN1','40DN2','40DN3','40DN4',"40DN5",'5DN1','5DN2','5DN3','5DN4',"5DN5","SolventBlank1")
###5 vs 40 GFP
experiment_2_names <- c('40GFP1','40GFP2','40GFP3','40GFP4',"40GFP5",'5GFP1','5GFP2','5GFP3','5GFP4',"5GFP5","SolventBlank1")
#
# ##40 DP vs GFP
experiment_3_names <- c('42C1','42C2','42C3','42C4',"42C5",
'7C1','7C2','7C3','7C4',"7C5",
"SolventBlank1")
# ##40 DP vs DN
# experiment_4_names <- c('40DP1','40DP2','40DP3','40DP4',"40DP5",'40DN1','40DN2','40DN3','40DN4',"40DN5", "SolventBlank1")
# ##40GFP vs DN
experiment_4_names <- c('40GFP1','40GFP2','40GFP3','40GFP4',"40GFP5",'40DN1','40DN2','40DN3','40DN4',"40DN5","SolventBlank1")
##40 GFP vs DN
experiment_5_names <- c('40DN1','40DN2','40DN3','40DN4',"40DN5",'40GFP1','40GFP2','40GFP3','40GFP4',"40GFP5", "SolventBlank1")
#40 DP vs 5DP
# experiment_6_names <- c('40DP1','40DP2','40DP3','40DP4',"40DP5",'5DP1','5DP2','5DP3','5DP4',"5DP5", "SolventBlank1")
##40 e vs 40 C
experiment_7_names <- c('42E1','42E2','42E3','42E4',"42E5", '42C1','42C2','42C3','42C4',"42C5", "SolventBlank1")
##42E vs 7 E
experiment_8_names <- c('42E1','42E2','42E3','42E4',"42E5",'7E1','7E2','7E3','7E4',"7E5", "SolventBlank1")
###7E vs 7C
experiment_9_names <- c('7E1','7E2','7E3','7E4',"7E5",'7C1','7C2','7C3','7C4',"7C5", "SolventBlank1")
###5GFP vs 5DN
experiment_10_names <- c('5GFP1','5GFP2','5GFP3','5GFP4',"5GFP5",'5DN1','5DN2','5DN3','5DN4',"5DN5", "SolventBlank1")
###7E vs 40C
experiment_11_names <- c('7E1','7E2','7E3','7E4',"7E5",'42C1','42C2','42C3','42C4',"42C5", "SolventBlank1")
###7E vs 40C
experiment_11_names <- c('7E1','7E2','7E3','7E4',"7E5",'42C1','42C2','42C3','42C4',"42C5", "SolventBlank1")
##40 DP vs GFP
experiment_12_names <- c('40DP1','40DP2','40DP3','40DP4',"40DP5",'40GFP1','40GFP2','40GFP3','40GFP4',"40GFP5", "SolventBlank1")
##40 DP vs DN
experiment_13_names <- c('40DP1','40DP2','40DP3','40DP4',"40DP5",'40DN1','40DN2','40DN3','40DN4',"40DN5", "SolventBlank1")
experiment_14_names <- c('40DP1','40DP2','40DP3','40DP4',"40DP5",'5GFP1','5GFP2','5GFP3','5GFP4',"5GFP5", "SolventBlank1")
title_for_plot_1 <- "40DN_vs_5DN_other_lipids"
title_for_plot_2 <- "40GFP_vs_5GFP_other_lipids"
title_for_plot_3 <- "42C_vs_7C_other_lipids"
title_for_plot_4 <- "40GFP_vs_40DN_other_lipids"
title_for_plot_5 <- "40DN_vs_40GFP_other_lipids"
title_for_plot_6 <- "40DP_vs_5DP_other_lipids"
title_for_plot_7 <- "42E_vs_42C_other_lipids"
title_for_plot_8 <- "42E_vs_7E_other_lipids"
title_for_plot_9 <- "7E_vs_7C_other_lipids"
title_for_plot_10 <- "5GFP_vs_5DN_other_lipids"
title_for_plot_11 <- "7E_vs_42C_other_lipids"
title_for_plot_12 <- "40DP_vs_40GFP_other_lipids"
title_for_plot_13 <- "40DP_vs_40DN_other_lipids"
title_for_plot_14 <- "40DP_vs_5GFP_other_lipids"
read_lipids <- function(prefix, marker, exp_names, types, add_Blank = NULL) {
lapply(names(types), function(type){
dir_name = paste0(prefix, "/")
# dir_name = paste0(prefix, "/", type, "/")
# suffix = paste0("_", types[[type]], "_results.xlsx")
suffix = "_12082022_results.xlsx"
all_names <- lapply(exp_names, function(n) {
file_name = paste0(dir_name,types[[type]],"_",n, suffix)
read_xlsx(file_name) %>%
dplyr::rename(lipid = `Lipid name`) %>%
dplyr::rename(!!n := `Total Intensity`) %>%
mutate(type = type) %>%
na.omit
})
if (!is.null(add_Blank)) {
Blank = read_xlsx(paste0(dir_name, add_Blank, suffix)) %>%
dplyr::rename(lipid = `Lipid name`) %>%
dplyr::rename(!!add_Blank := `Total Intensity`) %>%
mutate(type = type) %>%
na.omit
all_names = append(all_names, list(Blank))
}
Reduce(function(x, y) merge(x, y), all_names)
}) %>% bind_rows() %>% as_tibble() %>% filter(!grepl("STD_", lipid))
}
cells_lipid_expr_1 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_1_names, lipid_types
)
cells_lipid_expr_2 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_2_names, lipid_types
)
cells_lipid_expr_3 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_3_names, lipid_types
)
cells_lipid_expr_4 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_4_names, lipid_types
)
cells_lipid_expr_5 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_5_names, lipid_types
)
# cells_lipid_expr_6 = read_lipids(
# "fly_brain_12_8_22/results", "MEDIA",
# experiment_6_names, lipid_types
# )
cells_lipid_expr_7 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_7_names, lipid_types
)
#
cells_lipid_expr_8 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_8_names, lipid_types
)
cells_lipid_expr_9 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_9_names, lipid_types
)
cells_lipid_expr_10 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_10_names, lipid_types
)
cells_lipid_expr_11 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_11_names, lipid_types
)
cells_lipid_expr_12 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_12_names, lipid_types
)
cells_lipid_expr_13 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_13_names, lipid_types
)
cells_lipid_expr_14 = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
experiment_14_names, lipid_types
)
PCA_names = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, lipid_types
)
PCA_names_to_parse_No_Neurons
PCA_names_No_Neurons = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse_No_Neurons, lipid_types
)
TAG = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("TAG1" = "TAG1", "TAG2" = "TAG2")
)
write_csv(TAG,"heatmap_data_files/TAG_part4.csv")
FFA = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("FFA"="FFA")
)
write_csv(FFA,"heatmap_data_files/FFA_part3.csv")
CE = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("CE"="CE")
)
write_csv(CE,"heatmap_data_files/CE_part3.csv")
CER = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("CER"="CER")
)
write_csv(CER,"heatmap_data_files/CER_part3.csv")
PCandSM = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("PCandSM"="PCandSM")
)
write_csv(PCandSM,"heatmap_data_files/PCandSM_part3.csv")
PG = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("PG"="PG")
)
write_csv(PG,"heatmap_data_files/PG_part3.csv")
PE = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("PE"="PE")
)
write_csv(PE,"heatmap_data_files/PE_part3.csv")
PI = read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("PI"="PI")
)
write_csv(PI,"heatmap_data_files/PI_part3.csv")
AC= read_lipids(
"fly_brain_12_8_22/results", "MEDIA",
PCA_names_to_parse, c("AC"="AC")
)
write_csv(AC,"heatmap_data_files/AC_part3.csv")
# PS = read_lipids(
# "fly_brain_12_8_22/results", "MEDIA",
# PCA_names_to_parse, c("PS"="PS")
# )
# write_csv(PS,"heatmap_data_files/PS_part3.csv")
library(writexl)
#
# write_xlsx(x = blank_names_data, path = "Blanks_8_2_22.xlsx", col_names = TRUE)
write_xlsx(x = PCA_names, path = "Fly_Brain_Intensities_other_lipids.xlsx", col_names = TRUE)
write_xlsx(x = PCA_names_No_Neurons, path = "Fly_Brain_Intensities_other_lipids_No_Neuron.xlsx", col_names = TRUE)
library(edgeR)
#
# Groups for experiment 1
gr_expr_5 = c("GR1","GR1","GR1", "GR1","GR1","GR2","GR2","GR2", "GR2","GR2",
"SolventBlank1") %>%
factor(levels = c("SolventBlank1", "GR1", "GR2"))
design_expr_5 = model.matrix(~gr_expr_5)
contrasts_expr_5 = makeContrasts(
H = gr_expr_5GR1 - gr_expr_5GR2,
levels = design_expr_5
)
#
# gr_expr_1 = c("5DN","5DN","5DN","5DN","5DN", "40DN","40DN","40DN","40DN","40DN",
# "SolventBlank1") %>%
# factor(levels = c("SolventBlank1", "5DN", "40DN"))
#
#
#
# design_expr_1 = model.matrix(~gr_expr_1)
#
# contrasts_expr_1 = makeContrasts(
# H = gr_expr_15DN - gr_expr_140DN,
# levels = design_expr_1
# )
# # contrasts_expr_1 = makeContrasts(
# # H = gr_expr_1Control3x - gr_expr_1APIblock,
# # levels = design_expr_1
# # )
#
#
# # Groups for experiment 1
# gr_expr_2 = c("5GFP","5GFP","5GFP","5GFP","5GFP","40GFP","40GFP","40GFP","40GFP","40GFP",
# "SolventBlank1") %>%
# factor(levels = c("SolventBlank1", "5GFP", "40GFP"))
#
#
#
# design_expr_2 = model.matrix(~gr_expr_2)
#
# contrasts_expr_2 = makeContrasts(
# H = gr_expr_25GFP - gr_expr_240GFP,
# levels = design_expr_2
# )
#
#
#
# # Groups for experiment 1
# gr_expr_3 = c("DP","DP","DP", "DP","DP","GFP","GFP","GFP", "GFP","GFP",
# "SolventBlank1") %>%
# factor(levels = c("SolventBlank1", "DP", "GFP"))
#
#
#
# design_expr_3 = model.matrix(~gr_expr_3)
#
# contrasts_expr_3 = makeContrasts(
# H = gr_expr_340DP - gr_expr_340GFP,
# levels = design_expr_3
# )
#
#
#
# # Groups for experiment 1
# gr_expr_4 = c("DP","DP","DP", "DP","DP","DN","DN","DN", "DN","DN",
# "SolventBlank1") %>%
# factor(levels = c("SolventBlank1", "DP", "DN"))
#
#
#
# design_expr_4 = model.matrix(~gr_expr_4)
#
# contrasts_expr_4 = makeContrasts(
# H = gr_expr_4DP - gr_expr_4DN,
# levels = design_expr_4
# )
#
#
#
#
#
#
#
#
# # Groups for experiment 1
# gr_expr_5 = c("GFP","GFP","GFP", "GFP","GFP","DN","DN","DN", "DN","DN",
# "SolventBlank1") %>%
# factor(levels = c("SolventBlank1", "GFP", "DN"))
#
#
#
# design_expr_5 = model.matrix(~gr_expr_5)
#
# contrasts_expr_5 = makeContrasts(
# H = gr_expr_5GFP - gr_expr_5DN,
# levels = design_expr_5
# )
#
perform_analysis_raw <- function(counts, design_mat, gr) {
data.edgeR <- DGEList(counts = counts %>%
na.omit %>%
mutate(lipid = make.unique(lipid)) %>%
select(-Transition, -type) %>%
column_to_rownames("lipid"),
group = gr
)
data.edgeR <- calcNormFactors(data.edgeR, method="TMM")
data.edgeR <- estimateCommonDisp(data.edgeR, design=design_mat)
data.edgeR
}
calculate_significance <- function(dge, contrast) {
dge %>%
glmFit() %>%
glmLRT(contrast = contrast)
}
#
# experiment_1_helper <- function(df) {
# df %>%
# perform_analysis_raw(design_expr_1, gr_expr_1) %>%
# calculate_significance(contrasts_expr_1) %>%
# topTags(1500000) %>%
# as.data.frame() %>%
# rownames_to_column("lipid") %>%
# as_tibble()
#
# }
#
# experiment_2_helper <- function(df) {
# df %>%
# perform_analysis_raw(design_expr_2, gr_expr_2) %>%
# calculate_significance(contrasts_expr_2) %>%
# topTags(1500000) %>%
# as.data.frame() %>%
# rownames_to_column("lipid") %>%
# as_tibble()
#
# }
#
#
#
#
# experiment_3_helper <- function(df) {
# df %>%
# perform_analysis_raw(design_expr_3, gr_expr_3) %>%
# calculate_significance(contrasts_expr_3) %>%
# topTags(1500000) %>%
# as.data.frame() %>%
# rownames_to_column("lipid") %>%
# as_tibble()
#
# }
#
#
#
#
# experiment_4_helper <- function(df) {
# df %>%
# perform_analysis_raw(design_expr_4, gr_expr_4) %>%
# calculate_significance(contrasts_expr_4) %>%
# topTags(1500000) %>%
# as.data.frame() %>%
# rownames_to_column("lipid") %>%
# as_tibble()
#
# }
#
experiment_5_helper <- function(df) {
df %>%
perform_analysis_raw(design_expr_5, gr_expr_5) %>%
calculate_significance(contrasts_expr_5) %>%
topTags(1500000) %>%
as.data.frame() %>%
rownames_to_column("lipid") %>%
as_tibble()
}
# perform_analysis_raw(design_expr_3, gr_expr_3)
#
#
# calculate_significance(contrasts_expr_2)
#
cl_e1_tbl <-
cells_lipid_expr_1 %>%
experiment_5_helper
cl_e1_tbl
cl_e2_tbl <-
cells_lipid_expr_2 %>%
experiment_5_helper
cl_e2_tbl
#
cl_e3_tbl <-
cells_lipid_expr_3 %>%
experiment_5_helper
cl_e3_tbl
#
#
#
cl_e4_tbl <-
cells_lipid_expr_4 %>%
experiment_5_helper
cl_e4_tbl
cl_e5_tbl <-
cells_lipid_expr_5 %>%
experiment_5_helper
cl_e5_tbl
# cl_e6_tbl <-
# cells_lipid_expr_6 %>%
# experiment_5_helper
cl_e7_tbl <-
cells_lipid_expr_7 %>%
experiment_5_helper
cl_e8_tbl <-
cells_lipid_expr_8 %>%
experiment_5_helper
cl_e9_tbl <-
cells_lipid_expr_9 %>%
experiment_5_helper
cl_e10_tbl <-
cells_lipid_expr_10 %>%
experiment_5_helper
cl_e11_tbl <-
cells_lipid_expr_11 %>%
experiment_5_helper
cl_e12_tbl <-
cells_lipid_expr_12 %>%
experiment_5_helper
cl_e13_tbl <-
cells_lipid_expr_13 %>%
experiment_5_helper
cl_e14_tbl <-
cells_lipid_expr_14 %>%
experiment_5_helper
make_volcano_plot <- function(df, title) {
df %>%
mutate(sig = factor(FDR < 0.10)) %>%
ggplot(aes(logFC, -log10(FDR), color = sig)) +
geom_point() +
scale_color_manual(values = c("FALSE" = "black", "TRUE" = "red")) +
guides(color = F) +
ggtitle(title)
}
cl_e1_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_1,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_1,".png",sep=''))
cl_e2_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_2,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_2,".png",sep=''))
#
cl_e3_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_3,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_3,".png",sep=''))
cl_e4_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_4,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_4,".png",sep=''))
cl_e5_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_5,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_5,".png",sep=''))
#
# cl_e6_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_6,sep=''))
# ggsave(paste("plots/Volcano_Plot_",title_for_plot_6,".png",sep=''))
#
cl_e7_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_7,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_7,".png",sep=''))
cl_e8_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_8,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_8,".png",sep=''))
cl_e9_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_9,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_9,".png",sep=''))
cl_e10_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_10,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_10,".png",sep=''))
cl_e11_tbl %>% make_volcano_plot(paste("Volcano_Plot_",title_for_plot_11,sep=''))
ggsave(paste("plots/Volcano_Plot_",title_for_plot_11,".png",sep=''))
write_summary_and_results <- function(tbl, df, name) {
tbl %>%
merge(df) %>%
as_tibble() %>%
arrange(FDR) -> results
write_csv(results, paste0("results/", name, "_full.csv"))
results %>%
group_by(type) %>%
summarise(Down_regulated = sum(logFC < 0 & FDR < 0.1),
Up_regulated = sum(logFC > 0 & FDR < 0.1)) %>%
write_csv(paste0("results/", name, "_summary.csv"))
}
dir.create("results", F)
cl_e1_tbl %>% write_summary_and_results(cells_lipid_expr_1, title_for_plot_1)
cl_e2_tbl %>% write_summary_and_results(cells_lipid_expr_2, title_for_plot_2)
#
cl_e3_tbl %>% write_summary_and_results(cells_lipid_expr_3, title_for_plot_3)
#
cl_e4_tbl %>% write_summary_and_results(cells_lipid_expr_4, title_for_plot_4)
cl_e5_tbl %>% write_summary_and_results(cells_lipid_expr_5, title_for_plot_5)
#
#
# cl_e6_tbl %>% write_summary_and_results(cells_lipid_expr_6, title_for_plot_6)
cl_e7_tbl %>% write_summary_and_results(cells_lipid_expr_7, title_for_plot_7)
cl_e8_tbl %>% write_summary_and_results(cells_lipid_expr_8, title_for_plot_8)
cl_e9_tbl %>% write_summary_and_results(cells_lipid_expr_9, title_for_plot_9)
cl_e10_tbl %>% write_summary_and_results(cells_lipid_expr_10, title_for_plot_10)
cl_e11_tbl %>% write_summary_and_results(cells_lipid_expr_11, title_for_plot_11)
cl_e12_tbl %>% write_summary_and_results(cells_lipid_expr_12, title_for_plot_12)
cl_e13_tbl %>% write_summary_and_results(cells_lipid_expr_13, title_for_plot_13)
cl_e14_tbl %>% write_summary_and_results(cells_lipid_expr_14, title_for_plot_14)
get_DE_lipids <- function(counts, design_mat, gr, contrasts, p.value = .1) {
dls <-
counts %>%
perform_analysis_raw(design_mat, gr) %>%
calculate_significance(contrasts) %>%
decideTestsDGE(p.value = p.value)
rownames(dls)[dls %>% as.logical()]
}
make_pca_plot <- function(tp, design_mat, gr, contrasts,
title = "PCA plot",
ellipse = T, var.axes = F,
labels = T) {
print(labels)
print(labels)
tp_edger <-
tp %>%
get_DE_lipids(design_mat, gr, contrasts)
if(length(tp_edger) == 0) {
cat("No significant lipids for ", title)
return()
}
if(length(tp_edger) == 1) {
cat("Single significant lipids for ", title, " is ", tp_edger[1])
return()
}
tp %>%
na.omit %>%
mutate(lipid = make.unique(lipid)) %>%
filter(lipid %in% tp_edger) %>%
select(-Transition, -type, -SolventBlank1) %>%
column_to_rownames("lipid") %>%
as.matrix() %>%
t %>%
prcomp(center = T, scale = T) ->
prcomp_data
groups = NULL
tp %>%
select(-Transition, -type, -SolventBlank1, -lipid) %>%
colnames() ->
labels.tmp
groups = substr(labels.tmp, 1, 2)
print(groups)
groups = gr[-length(gr)]
print(groups)
print(substr(labels.tmp, 1, 4))
if (!is.null(labels)) {
labels = labels.tmp
}
prcomp_data %>%
ggbiplot(ellipse = ellipse,
labels = labels,
groups = groups,
var.axes = var.axes
) +
ggtitle(title) +
cowplot::theme_cowplot()
}
make_pca_plot2 <- function(tp, design_mat, gr, contrasts,
title = "PCA plot",
ellipse = T, var.axes = F,
labels = T) {
print(labels)
print(labels)
tp_edger <-
tp %>%
get_DE_lipids(design_mat, gr, contrasts)
if(length(tp_edger) == 0) {
cat("No significant lipids for ", title)
return()
}
if(length(tp_edger) == 1) {
cat("Single significant lipids for ", title, " is ", tp_edger[1])
return()
}
tp %>%
na.omit %>%
mutate(lipid = make.unique(lipid)) %>%
filter(lipid %in% tp_edger) %>%
select(-Transition, -type, -SolventBlank1) %>%
column_to_rownames("lipid") %>%
as.matrix() %>%
t %>%
prcomp(center = T, scale = T) ->
prcomp_data
groups = NULL
tp %>%
select(-Transition, -type, -SolventBlank1, -lipid) %>%
colnames() ->
labels.tmp
groups = substr(labels.tmp, 1, 4)
groups = gr[-length(gr)]
print(groups)
print(substr(labels.tmp, 1, 5))
if (!is.null(labels)) {
labels = labels.tmp
}
print(labels)
prcomp_data %>%
ggbiplot(ellipse = ellipse,
labels = labels,
groups = groups,
var.axes = var.axes
) +
ggtitle(title) +
cowplot::theme_cowplot()
}
source("ggbiplot.R")
get_DE_lipids3 <- function(counts, design_mat, gr, contrasts, p.value = .1) {
dls <-
counts %>%
perform_analysis_raw(design_mat, gr) %>%
calculate_significance(contrasts) %>%
decideTestsDGE(p.value = p.value)
rownames(dls)[dls %>% as.logical()]
}
make_pca_plot3 <- function(tp, design_mat, gr, contrasts,
title = "PCA plot",
ellipse = T, var.axes = F,
labels = T) {
print(labels)
print(labels)
tp_edger <-
tp %>%
get_DE_lipids3(design_mat, gr, contrasts)
if(length(tp_edger) == 0) {
cat("No significant lipids for ", title)
return()
}
if(length(tp_edger) == 1) {
cat("Single significant lipids for ", title, " is ", tp_edger[1])
return()
}
tp %>%
na.omit %>%
mutate(lipid = make.unique(lipid)) %>%
filter(lipid %in% tp_edger) %>%
select(-Transition, -type, -SolventBlank1) %>%
column_to_rownames("lipid") %>%
as.matrix() %>%
t %>%
prcomp(center = T, scale = T) ->
prcomp_data
groups = NULL
tp %>%
select(-Transition, -type, -SolventBlank1, -lipid) %>%
colnames() ->
labels.tmp
groups = substr(labels.tmp, 1, 4)
groups = gr[-length(gr)]
print(groups)
print(substr(labels.tmp, 1, 5))
if (!is.null(labels)) {
labels = labels.tmp
}
print(labels)
labels = c("N","N","N","N","N","-","-","-","-","-")
prcomp_data %>%
ggbiplot(ellipse = ellipse,
labels = labels,
groups = groups,
var.axes = var.axes
) +
ggtitle(title) +
cowplot::theme_cowplot()
}
#
#
#
#
#
cells_lipid_expr_1 %>%
make_pca_plot3(design_expr_5, gr_expr_5, contrasts_expr_5, paste("PCA_Plot_",title_for_plot_1,sep=''))
ggsave(paste("plots2/PCA__FDR_",title_for_plot_1,".pdf",sep=''))
cells_lipid_expr_2 %>%
make_pca_plot3(design_expr_5, gr_expr_5, contrasts_expr_5, paste("PCA_Plot_",title_for_plot_2,sep=''))
ggsave(paste("plots2/PCA_",title_for_plot_2,".pdf",sep=''))
#
#
# cells_lipid_expr_3 %>%
# make_pca_plot(design_expr_5, gr_expr_5, contrasts_expr_5, paste("PCA_Plot_",title_for_plot_3,sep=''))
# ggsave(paste("plots2/PCA_",title_for_plot_3,".pdf",sep=''))
# #
# #
# #
# cells_lipid_expr_4 %>%
# make_pca_plot2(design_expr_5, gr_expr_5, contrasts_expr_5, paste("PCA_Plot_",title_for_plot_4,sep=''))
# ggsave(paste("plots2/PCA_",title_for_plot_4,".pdf",sep=''))
#
cells_lipid_expr_5 %>%
make_pca_plot3(design_expr_5, gr_expr_5, contrasts_expr_5, paste("PCA_Plot_",title_for_plot_5,sep=''))
ggsave(paste("plots2/PCA_FDR_",title_for_plot_5,".pdf",sep=''))
#
# # cells_lipid_expr_6 %>%
# # make_pca_plot(design_expr_5, gr_expr_5, contrasts_expr_5, paste("PCA_Plot_",title_for_plot_6,sep=''))
# # ggsave(paste("plots/PCA_",title_for_plot_6,".svg",sep=''))
# #
#
#
#
cells_lipid_expr_7 %>%
make_pca_plot3(design_expr_5, gr_expr_5, contrasts_expr_5, paste("PCA_Plot_",title_for_plot_7,sep=''))
ggsave(paste("plots2/PCA_FDR_",title_for_plot_7,".pdf",sep=''))
#
#
# cells_lipid_expr_8 %>%
# make_pca_plot(design_expr_5, gr_expr_5, contrasts_expr_5, paste("PCA_Plot_",title_for_plot_8,sep=''))
# ggsave(paste("plots2/PCA_",title_for_plot_8,".pdf",sep=''))
#