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cying111 committed Nov 28, 2024
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81 changes: 5 additions & 76 deletions manuscript/code/data analysis and visualization/Figure_1.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -52,8 +52,6 @@ saveDate <- general_list$saveDate
# Fig. 1b-c
```{r}
## Figure 1 ========================
#valueLabels <- c("Illumina","RNA","PCR-free cDNA","cDNA")
#cellLines <- c('Hct116','HepG2','K562','A549','MCF7',"H9","HEYA8","Hek293T","HN1NPC7")
plotData_wide <- samples[,list(nrun=length(runname)), by = list(cancer_type,cellLine, protocol_type)]
plotData_wide[, protocol_type := gsub("-SMRTcell","",protocol_type)]
plotData_wide[, cellLine_general := ifelse(cellLine %in% cellLines, cellLine, cancer_type)]
Expand All @@ -70,15 +68,14 @@ plotData_wide <- plotData_wide[order(ttrun, cancer_type, nrun, decreasing = TRUE
plotData_wide
#cellLineVar <- plotData_wide$cellLine_general
cancer_typeVar <- unique(plotData_wide$cancer_type)
cancer_typeCol <- c(brewer.pal(9,"Paired"),brewer.pal(8,"Accent")[8:7])
p_core_cellLine <- ggplot(plotData_wide[cellLine_general %in% cellLines], aes(x = reorder(cellLine_general,-nrun), y = nrun, fill = factor(protocol_type, levels = protocolVec)))+
geom_bar(stat = "identity",alpha = 0.5)+
ylab("Number of replicates")+
xlab("Cell lines")+
#coord_flip()+
scale_y_discrete(limits = c(0,5,10,15,20,25))+
scale_fill_manual(values = protocolCol,
labels = protocolLabel,
Expand All @@ -90,25 +87,13 @@ p_core_cellLine
pdf(paste0(wkdir,"figure1/Number_of_runsCellLines",saveDate,".pdf"), width = 6, height = 4)
print(p_extended)
dev.off()
# protocolCol <- adjustcolor(brewer.pal(8,"Paired")[1:4],0.7)
# protocolVec <- c("directRNA","directcDNA","cDNA","Illumina")
# protocolLabel <- c("RNA","PCR-free cDNA","cDNA","Illumina")
```




## main figure 1b
```{r}
## core data set bar plot =====================
# pdf(paste0("figures/Number_of_runsCellLinesCoreDataset",saveDate,".pdf"), width = 6, height = 4)
# print(p)
# dev.off()
# ## extended data set bar plot =====================
# ## include extended cell lines by setting al cell lines different from core cellLines
plotData_wide_all <- samples[,list(nrun=length(runname)), by = list(cellLine)]
plotData_wide_all[, cellLine_general := ifelse(!(cellLine %in% cellLines), "others", cellLine)]
plotData_wide_all[, nrun := sum(nrun), by = cellLine_general]
Expand All @@ -119,24 +104,18 @@ p_extended <- ggplot(plotData_wide_all, aes(x = reorder(cellLine_general,-nrun),
geom_bar(stat = "identity",alpha = 0.5, col = "white", fill = "lightblue")+
ylab("Number of replicates")+
xlab("Cell lines")+
#coord_flip()+
scale_y_continuous(breaks = c(0,5,10,15,20,25))+
# scale_fill_manual(values = cancer_typeCol,
# limits = c(cellLines,"others"),
# name = "Tissues")+
theme_classic()+
theme(axis.text.x = element_text(angle = (90), hjust = 0))
p_extended
# # scale_x_discrete(breaks = setdiff(plotData_wide$cellLine, unique(plotData_wide$cancer_type)))+
#
pdf(paste0(wkdir,"figure1/Number_of_runsCellLinesExtendedDataset",saveDate,".pdf"), width = 6, height = 4)
print(p_extended)
dev.off()
```


```{r spike-in-samples}
samples_wSpikein[grepl("PacBio", runname), RNAcontent := "sequin MixA V2 E2 SIRV-4"]
samples_wSpikein[, `:=`(sequin_mixa_v1 = grepl("sequin",RNAcontent)&grepl("v1",RNAcontent),
sequin_mixa_v2 = grepl("sequin",RNAcontent)&grepl("V2",RNAcontent),
Expand All @@ -150,14 +129,12 @@ plotData_spikein <- unique(samples_wSpikein[, list(sequin_mixa_v1 = sum(sequin_m
by = NULL)
plotData <- melt(plotData_spikein, id.vars = "protocol_type", measure.vars = colnames(plotData_spikein)[-1])
setnames(plotData, c("variable","value"),c("cellLine_general","nrun"))
```


```{r}
plotData_wide <- rbindlist(list(plotData_wide,plotData), fill = TRUE)
plotData_wide[, ord := sprintf("%02i", frank(plotData_wide, nrun, ties.method = "first"))]
```


Expand All @@ -175,12 +152,6 @@ p_samples <- ggplot(plotData_wide[!grepl("sequin|sirv",cellLine_general)], aes(x
ylab("Number of replicates")+
xlab("Cell lines")+
coord_flip()+
# facet_wrap(~protocol_type, scales = "free", nrow = 1)+
#scale_y_discrete(limits = c(0,5,10,15,20,25))+
# scale_fill_manual(values = protocolCol,
# labels = protocolLabel,
# limits = protocolVec,
# name = "Protocols")+
theme_classic()+
# rotate x-axis labels
theme(axis.text.x = element_text(angle = 90, hjust=1, vjust=.5))
Expand All @@ -204,12 +175,6 @@ p_spikein <- ggplot(plotData_wide[grepl("sequin|sirv",cellLine_general)], aes(x
ylab("Number of replicates")+
xlab("Cell lines")+
coord_flip()+
# facet_wrap(~protocol_type, scales = "free", nrow = 1)+
#scale_y_discrete(limits = c(0,5,10,15,20,25))+
# scale_fill_manual(values = protocolCol,
# labels = protocolLabel,
# limits = protocolVec,
# name = "Protocols")+
theme_classic()+
# rotate x-axis labels
theme(axis.text.x = element_text(angle = 90, hjust=1, vjust=.5))
Expand All @@ -223,46 +188,29 @@ dev.off()
```{r}
p_samples <- ggplot(plotData_wide[!grepl("sequin|sirv",cellLine_general)], aes(x = cellLine_general, y = protocol_type))+
geom_point(aes(size = nrun), alpha = 0.7, color = "lightblue")+
#scale_x_discrete(labels = plotData_wide[, setNames(as.character(cellLine_names), ord)]) +
scale_size_continuous(limits = c(1, 15), range = c(1,15), breaks = c(1,5,10,15)) +
geom_text(aes(label = nrun))+
ylab("")+
xlab("Cell lines")+
coord_flip()+
# facet_wrap(~protocol_type, scales = "free", nrow = 1)+
#scale_y_discrete(limits = c(0,5,10,15,20,25))+
# scale_fill_manual(values = protocolCol,
# labels = protocolLabel,
# limits = protocolVec,
# name = "Protocols")+
theme_minimal()+
# rotate x-axis labels
theme(#axis.text.x = element_text(angle = 90, hjust=1, vjust=.5),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())+ labs(x=NULL)#,plot.margin=unit(c(1,1,0,1),"cm")
theme(axis.text.x=element_blank(),
axis.ticks.x=element_blank())+ labs(x=NULL)
p_spikein <- ggplot(plotData_wide[grepl("sequin|sirv",cellLine_general)], aes(x = cellLine_names, y = protocol_type))+
geom_point(aes(size = nrun), alpha = 0.7, color = "lightblue")+
#scale_x_discrete(labels = plotData_wide[, setNames(as.character(cellLine_names), ord)]) +
scale_size_continuous(limits = c(1, 15), range = c(1,15), breaks = c(1,5,10,15)) +
geom_text(aes(label = nrun))+
ylab("Number of replicates")+
xlab("Cell lines")+
coord_flip()+
# facet_wrap(~protocol_type, scales = "free", nrow = 1)+
#scale_y_discrete(limits = c(0,5,10,15,20,25))+
# scale_fill_manual(values = protocolCol,
# labels = protocolLabel,
# limits = protocolVec,
# name = "Protocols")+
theme_minimal()+
# rotate x-axis labels
theme(axis.text.x = element_text(angle = 90, hjust=1, vjust=.5))#,plot.margin=unit(c(0,1,1,1),"cm")
```
```{r, fig.width = 8, fig.height = 8}
library(ggpubr)
#grid.arrange(p_samples, p_spikein,heights=c(1.8,1))
#ggarrange(p_samples, p_spikein, nrow = 2, common.legend = TRUE,legend = "bottom",heights = c(2,1),align = "hv")# + rremove("xlab")+rremove("x.axis")+rremove("x.text")+rremove("x.ticks")
pdf(paste0(wkdir,"figure1/Number_of_runsCellLinesExtendedDataset",saveDate,"_dotplot.pdf"), width = 8, height = 8)
grid.arrange(p_samples, p_spikein,heights=c(1.8,1))
dev.off()
Expand All @@ -281,23 +229,6 @@ blank_theme <- theme_minimal()+
plot.title=element_text(size=14, face="bold")
)
## core data set pie chart ==============
# df <- data.table(table(samples[cellLine %in% cellLines]$protocol_type)) #[cellLine %in% cellLines]
# df[, V1 := gsub("-SMRTcell","", V1)]
# df$pos <- c(108,82,45,10)
# pie <- ggplot(df, aes(x="", y=N, fill=V1))+
# geom_bar(width = 1, stat = "identity")+coord_polar("y", start=0)
# library(scales)
# p <- pie + scale_fill_manual(values = protocolCol,
# breaks = protocolVec,
# labels = protocolLabel, name = "Protocol") + blank_theme +
# theme(axis.text.x=element_blank()) +
# geom_text(aes(y = pos,
# label = N), size=5)
# pdf(paste0("figures/Number_of_runsProtocolCoreDataSet",saveDate,".pdf"), width = 6, height = 4)
# print(p)
# dev.off()
## extended data set pie chart ====================
df <- data.table(table(samples$protocol_type)) #[cellLine %in% cellLines]
df[, V1 := gsub("-SMRTcell","", V1)]
Expand Down Expand Up @@ -387,7 +318,6 @@ write.table(new_supp_table1, file ="supp_table1_sheet1.csv", row.names = FALSE,

# illumina samples
```{r}
new_supp_table1 <- unique(samplesRC_combined[(protocol_type_factor %in% c("Illumina"))&(!grepl("allSpikin",runname)), .(runname, total_reads)])
setnames(new_supp_table1, c("runname","total_reads"), c("Sample","Sequencing depth"))
Expand All @@ -397,7 +327,6 @@ write.table(new_supp_table1, file ="supp_table1_sheet2.csv", row.names = FALSE,

# pacbio samples
```{r}
new_supp_table1 <- unique(samplesRC_combined[(protocol_type_factor %in% c("PacBio"))&(!grepl("allSpikin",runname)), .(runname, total_reads)])
setnames(new_supp_table1, c("runname","total_reads"), c("Sample","Sequencing depth"))
Expand Down
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