403 lines
15 KiB
R
403 lines
15 KiB
R
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library(ggplot2)
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library(stringr)
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#####
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#This part of scripts produces the plots of alignment data. Only plasmid-aligned reverse reads were taken here.
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#For every sample was created a set of reads of equal capacity (min between all sample reads).
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#####
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#Uploading data in R
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t1<-read.csv("../custom_1_90_mapq.txt", sep=";")
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t2<-read.csv("../custom_2_87_mapq.txt", sep=";")
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t4<-read.csv("../custom_4_96_mapq.txt", sep=";")
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t5<-read.csv("../custom_5_92_mapq.txt", sep=";")
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t6<-read.csv("../custom_6_108_mapq.txt", sep=";")
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t7<-read.csv("../custom_7_97_mapq.txt", sep=";")
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tpol<-read.csv("../custom_pol_93_mapq.txt", sep=";")
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tp<-cbind(t1, "Sample" =1)
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tp<-rbind(tp, cbind(t2, "Sample" =2))
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tp<-rbind(tp, cbind(t4, "Sample" =4))
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tp<-rbind(tp, cbind(t5, "Sample" =5))
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tp<-rbind(tp, cbind(t6, "Sample" =6))
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tp<-rbind(tp, cbind(t7, "Sample" =7))
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tp<-rbind(tp, cbind(tpol, "Sample" =9))
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samples<-c(2, 4:7, 9)
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sample2<-subset(tp, Read==2&Sample==1)
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tp2<-sample2[sample(nrow(sample2), 20000),]
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for (i in samples) {
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sample2<-subset(tp, Read==2&Sample==i)
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tp2<-rbind(tp2, sample2[sample(nrow(sample2), 20000),])
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}
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rm(sample2, t1, t2, t4, t5, t6, t7, tpol)
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#GC-content
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ggplot(data = tp2, aes(x = GC)) +
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geom_density(stat = "density", fill = "pink", alpha = 0.5) +
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facet_wrap(~Sample, nrow = 3) +
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geom_vline(xintercept = 50, linetype="dotted") +
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xlim(25, 75) +
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ylim(0, 0.15) +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/gc.png", width = 2250, height = 1500, units = "px")
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#Mismatches per cycle of sequence
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df2<-data.frame("Cycles"=0, "Sample"=1)
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for (i in c(1:2, 4:7, 9)) {
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cyc <-subset(tp2, Sample == i)[,4]
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cyc <- as.numeric(unlist(strsplit(cyc,",")))
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df2<-rbind(df2, cbind("Cycles" = cyc, "Sample" =i))
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}
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df2<-df2[-1,]
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df2$Sample<-as.factor(df2$Sample)
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rm (cyc, i)
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ggplot(df2, aes(x = Cycles)) +
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geom_density(stat = "count", fill = "blue", alpha = 0.5) +
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#geom_line(stat = "count", fill = "blue", alpha = 0.5) +
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facet_wrap(~Sample, nrow = 3) +
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ggtitle("Mismatches per cycle") +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/mpc.png", width = 2250, height = 1500, units = "px")
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ggplot(df2, aes(x = Cycles)) +
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geom_density(stat = "density", fill = "blue", alpha = 0.5) +
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facet_wrap(~Sample, nrow = 3) +
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ggtitle("Mismatches per cycle") +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/mpc_density.png", width = 2250, height = 1500, units = "px")
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rm (df2)
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#Mismatches depending on GC-content
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mgc2<-cbind(tp2[, c("Count_SNPs", "Sample")], "GC" = round(tp2$GC))
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ggplot(mgc2, aes(x=GC, y=Count_SNPs)) +
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stat_summary(fun = sum, geom="line", linewidth = 0.5) +
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facet_wrap(~Sample, nrow = 3) +
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ggtitle("Mismatches/GC") +
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geom_vline(xintercept = 50, linetype="dotted") +
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theme_bw()+
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/mgc.png", width = 2250, height = 1500, units = "px")
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ggplot(mgc2, aes(x=GC, y=Count_SNPs)) +
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stat_summary(fun = mean, geom="line", size = 0.5) +
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facet_wrap(~Sample, nrow = 3) +
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ggtitle("Mismatches/GC") +
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geom_vline(xintercept = 50, linetype="dotted") +
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theme_bw()+
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/mgc_mean.png", width = 2250, height = 1500, units = "px")
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rm (mgc2)
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#Frequency of different types of mismatches
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mtype2 <- apply(tp2[, c(12:23)][tp2$Sample==1,], 2, sum)
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mtype2 <- data.frame("Sum" = mtype2)
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mtype2$type<-as.factor(colnames(tp2[, c(12:23)]))
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mtype2<-cbind(mtype2, "Sample" = 1)
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for (i in samples) {
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temp <- apply(tp2[, c(12:23)][tp2$Sample==i,], 2, sum)
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temp <- data.frame("Sum" = temp)
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temp$type<-as.factor(colnames(tp2[, c(12:23)]))
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temp<-cbind(temp, "Sample" = i)
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mtype2<-rbind(mtype2, temp)
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}
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ggplot(mtype2) +
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geom_line(aes(x = type, y = Sum, group = Sample)) +
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geom_point(aes(x = type, y = Sum)) +
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#facet_wrap(~Sample, nrow = 3, scales = "free_y") +
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facet_wrap(~Sample, nrow = 3, ) +
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ggtitle("Mismatch type") +
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theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
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ggsave("../report/images_read2/mt.png", width = 2250, height = 1500, units = "px")
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mtype2_2 <- apply(tp2[tp2$Sample==1, c(12:23)], 2, mean)
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mtype2_2 <- data.frame("mean" = mtype2_2)
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mtype2_2$type<-as.factor(colnames(tp2[, c(12:23)]))
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mtype2_2<-cbind(mtype2_2, "Sample" = 1)
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for (i in samples) {
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temp <- apply(tp2[tp2$Sample==i, c(12:23)], 2, mean)
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temp <- data.frame("mean" = temp)
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temp$type<-as.factor(colnames(tp2[, c(12:23)]))
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temp<-cbind(temp, "Sample" = i)
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mtype2_2<-rbind(mtype2_2, temp)
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}
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ggplot(mtype2_2) +
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geom_line(aes(x = type, y = mean, group = Sample)) +
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geom_point(aes(x = type, y = mean)) +
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#facet_wrap(~Sample, nrow = 3, scales = "free_y") +
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facet_wrap(~Sample, nrow = 3) +
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ggtitle("Mismatch type") +
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theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
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ggsave("../report/images_read2/mt_mean.png", width = 2250, height = 1500, units = "px")
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rm(mtype2, mtype2_2)
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#Number of deletions per sample
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delets2 <- tp2[tp2$Sample==1,][,10]
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delets2 <- unlist(strsplit(delets2,""))
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delets2<- delets2[delets2 %in% c(letters, LETTERS)]
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delets2<-cbind("Nucleotide"=delets2, "Sample" = 1)
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delets2<-data.frame(delets2)
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delets2$Nucleotide <- as.factor(delets2$Nucleotide)
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for (i in samples) {
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temp <- tp2[tp2$Sample==i,][,10]
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temp <- unlist(strsplit(temp,""))
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temp<- temp[temp %in% c(letters, LETTERS)]
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temp<-cbind("Nucleotide"=temp, "Sample" = i)
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temp<-data.frame(temp)
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temp$Nucleotide <- as.factor(temp$Nucleotide)
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delets2<-rbind(temp, delets2)
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}
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ggplot(delets2) +
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geom_bar(aes(x = Nucleotide), width = 0.25, fill = "orange") +
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facet_wrap(~Sample, nrow = 3, scales = "free_y") +
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#ylim(0, 1500) +
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ggtitle ("Deletes") +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/delets.png", width = 2250, height = 1500, units = "px")
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rm (delets2)
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#Number of insertions per sample
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inserts2 <- tp2[tp2$Sample==1,][,11]
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inserts2 <- unlist(strsplit(inserts2,""))
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inserts2<- inserts2[inserts2 %in% c(letters, LETTERS)]
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inserts2<-cbind("Nucleotide"=inserts2, "Sample" = 1)
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inserts2<-data.frame(inserts2)
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inserts2$Nucleotide <- as.factor(inserts2$Nucleotide)
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for (i in samples) {
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temp <- tp2[tp2$Sample==i,][,11]
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temp <- unlist(strsplit(temp,""))
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temp<- temp[temp %in% c(letters, LETTERS)]
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temp<-cbind("Nucleotide"=temp, "Sample" = i)
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temp<-data.frame(temp)
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temp$Nucleotide <- as.factor(temp$Nucleotide)
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inserts2<-rbind(temp, inserts2)
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}
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ggplot(inserts2) +
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ggtitle("Inserts") +
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geom_bar(aes(x = Nucleotide), width = 0.25, fill = "orange") +
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facet_wrap(~Sample, nrow = 2, scales = "free_y") +
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#ylim(0, 2000) +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/inserts.png", width = 2250, height = 1500, units = "px")
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rm (inserts2)
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#Mean, min and max values of insertions per sample
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insert_mean2<-subset(tp2, Sample == 1)[,7]
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insert_mean2<-cbind("Sample"=1, t(summary(insert_mean2)))
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for (i in samples) {
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temp<-subset(tp2, Mean_length_insert!=0 & Sample == i)[,7]
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temp<-cbind("Sample"=i, t(summary(temp)))
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insert_mean2<-rbind(insert_mean2, temp)
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}
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ggplot(data.frame(insert_mean2), aes(x = factor(Sample), y = Mean), size = 0.5) +
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geom_pointrange(aes(ymin = 0, ymax = Max.)) +
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scale_y_continuous(breaks = c(0:12), limits = c(0, 13)) +
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geom_point(aes(x = factor(Sample), y = 0), shape = 1) +
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geom_point(aes(x = factor(Sample), y = Max.), shape = 1) +
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ggtitle("Insert mean length") +
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scale_x_discrete(name = "Sample") +
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scale_y_continuous(name = "Length", breaks = seq(0, 18, 1)) +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/iml.png", width = 2250, height = 1500, units = "px")
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rm (insert_mean2)
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#Mean, min and max values of deletions per sample
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delete_mean2<-subset(tp2, Sample == 1)[,6]
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delete_mean2<-cbind("Sample"=1, t(summary(delete_mean2)))
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for (i in samples) {
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temp<-subset(tp2, Mean_length_del!=0 & Sample == i)[,6]
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temp<-cbind("Sample"=i, t(summary(temp)))
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delete_mean2<-rbind(delete_mean2, temp)
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}
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ggplot(data.frame(delete_mean2), aes(x = factor(Sample), y = Mean), size = 0.5) +
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geom_pointrange(aes(ymin = 0, ymax = Max.)) +
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scale_y_continuous(breaks = c(0:22), limits = c(0, 22)) +
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geom_point(aes(x = factor(Sample), y = 0), shape = 1) +
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geom_point(aes(x = factor(Sample), y = Max.), shape = 1) +
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ggtitle("Delete mean length") +
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scale_x_discrete(name = "Sample") +
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scale_y_continuous(name = "Length", breaks = seq(0, 12, 1)) +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/dml.png", width = 2250, height = 1500, units = "px")
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rm(delete_mean2)
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#Number of mismatches per sample
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ggplot(tp2, aes(x=Sample, y=Count_SNPs, group = 1)) +
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stat_summary(fun = mean, geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
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ggtitle("Mismatches per sample") +
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#geom_vline(xintercept = 50, linetype="dotted") +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/mps_mean.png", width = 2250, height = 1500, units = "px")
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ggplot(tp2, aes(x=Sample, y=Count_SNPs, group = 1)) +
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stat_summary(fun = sum, geom="point") +
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stat_summary(fun = sum, geom="line") +
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ggtitle("Mismatches per sample") +
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#geom_vline(xintercept = 50, linetype="dotted") +
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/mps.png", width = 2250, height = 1500, units = "px")
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#Number of deletions per cycle of sequence
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numbers_only <- function(x) !grepl("\\D", x)
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dels2 <- tp2[tp2$Sample==1,][,10]
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dels2 <- unlist(strsplit(dels2, split="|",fixed = TRUE))
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dels2 <- unlist(strsplit(dels2,","))
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dels2<- dels2[numbers_only(dels2)]
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dels2<-cbind("Num"=dels2, "Sample" = 1)
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dels2<-data.frame(dels2)
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for (i in samples) {
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temp <- tp2[tp2$Sample==i,][,10]
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temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
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temp <- unlist(strsplit(temp,","))
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temp<- temp[numbers_only(temp)]
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temp<-cbind("Num"=temp, "Sample" = i)
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temp<-data.frame(temp)
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dels2<-rbind(temp, dels2)
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}
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dels2$Num<-as.numeric(dels2$Num)
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ggplot(dels2, aes(x = Num)) +
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#geom_density(stat = "count", alpha = 0.5) +
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stat_count(geom="line", position="identity") +
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stat_count(geom="point", position="identity", size = 1) +
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facet_wrap(~Sample, nrow = 3, scales = "free_y") +
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#ylim(0, 1500) +
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ggtitle ("Deletes per cycle") +
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theme_bw()+
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theme(plot.title = element_text(hjust = 0.5))
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ggsave("../report/images_read2/dpc.png", width = 2250, height = 1500, units = "px")
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rm(dels2)
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#Number of insertions per cycle of sequence
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ins2 <- tp2[tp2$Sample==1,][,11]
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ins2 <- unlist(strsplit(ins2, split="|",fixed = TRUE))
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ins2 <- unlist(strsplit(ins2,","))
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ins2<- ins2[numbers_only(ins2)]
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ins2<-cbind("Num"=ins2, "Sample" = 1)
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ins2<-data.frame(ins2)
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for (i in samples) {
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temp <- tp2[tp2$Sample==i,][,11]
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temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
|
||
|
|
temp <- unlist(strsplit(temp,","))
|
||
|
|
temp<- temp[numbers_only(temp)]
|
||
|
|
temp<-cbind("Num"=temp, "Sample" = i)
|
||
|
|
temp<-data.frame(temp)
|
||
|
|
ins2<-rbind(temp, ins2)
|
||
|
|
}
|
||
|
|
ins2$Num<-as.numeric(ins2$Num)
|
||
|
|
ggplot(ins2, aes(x = Num)) +
|
||
|
|
stat_count(geom="line", position="identity") +
|
||
|
|
stat_count(geom="point", position="identity", size = 1) +
|
||
|
|
facet_wrap(~Sample, nrow = 3, scales = "free_y") +
|
||
|
|
#ylim(0, 1500) +
|
||
|
|
ggtitle ("Inserts per cycle") +
|
||
|
|
scale_x_continuous(breaks=seq(0, 150, 25))+
|
||
|
|
scale_y_continuous(drop=FALSE)
|
||
|
|
theme_bw()+
|
||
|
|
theme(plot.title = element_text(hjust = 0.5))
|
||
|
|
ggsave("../report/images_read2/ipc.png", width = 2250, height = 1500, units = "px")
|
||
|
|
rm (ins2)
|
||
|
|
|
||
|
|
#Number of deletions per sample
|
||
|
|
|
||
|
|
parse_delets2 <- tp2[tp2$Sample==1,][,10]
|
||
|
|
parse_delets2 <- unlist(strsplit(parse_delets2, split="|",fixed = TRUE))
|
||
|
|
parse_delets2<-cbind("Num"=parse_delets2, "Sample" = 1)
|
||
|
|
parse_delets2<-data.frame(parse_delets2)
|
||
|
|
for (i in samples) {
|
||
|
|
temp <- tp2[tp2$Sample==i,][,10]
|
||
|
|
temp <- unlist(strsplit(temp,split="|",fixed = TRUE))
|
||
|
|
temp<-cbind("Num"=temp, "Sample" = i)
|
||
|
|
temp<-data.frame(temp)
|
||
|
|
parse_delets2<-rbind(temp, parse_delets2)
|
||
|
|
}
|
||
|
|
ggplot(parse_delets2, aes(x=Sample, group = 1)) +
|
||
|
|
stat_count(geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
|
||
|
|
ggtitle("Deletes per sample") +
|
||
|
|
#geom_vline(xintercept = 50, linetype="dotted") +
|
||
|
|
theme(plot.title = element_text(hjust = 0.5))
|
||
|
|
ggsave("../report/images_read2/dps.png", width = 2250, height = 1500, units = "px")
|
||
|
|
rm (parse_delets2)
|
||
|
|
|
||
|
|
#Number of insertions per sample
|
||
|
|
|
||
|
|
parse_inserts2 <- tp2[tp2$Sample==1,][,11]
|
||
|
|
parse_inserts2 <- unlist(strsplit(parse_inserts2, split="|",fixed = TRUE))
|
||
|
|
parse_inserts2<-cbind("Num"=parse_inserts2, "Sample" = 1)
|
||
|
|
parse_inserts2<-data.frame(parse_inserts2)
|
||
|
|
for (i in samples) {
|
||
|
|
temp <- tp2[tp2$Sample==i,][,11]
|
||
|
|
temp <- unlist(strsplit(temp,split="|",fixed = TRUE))
|
||
|
|
temp<-cbind("Num"=temp, "Sample" = i)
|
||
|
|
temp<-data.frame(temp)
|
||
|
|
parse_inserts2<-rbind(temp, parse_inserts2)
|
||
|
|
}
|
||
|
|
ggplot(parse_inserts2, aes(x=Sample, group = 1)) +
|
||
|
|
stat_count(geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
|
||
|
|
ggtitle("Inserts per sample") +
|
||
|
|
#geom_vline(xintercept = 50, linetype="dotted") +
|
||
|
|
theme(plot.title = element_text(hjust = 0.5))
|
||
|
|
ggsave("../report/images_read2/ips.png", width = 2250, height = 1500, units = "px")
|
||
|
|
rm (parse_inserts2, temp)
|
||
|
|
|
||
|
|
#Frequency of insertion motifs per sample
|
||
|
|
|
||
|
|
insert_motifs2 <- tp2[tp2$Sample==1,][,11]
|
||
|
|
insert_motifs2 <- unlist(strsplit(insert_motifs2, split="|",fixed = TRUE))
|
||
|
|
insert_motifs2 <- unlist(strsplit(insert_motifs2,","))
|
||
|
|
insert_motifs2<- insert_motifs2[!numbers_only(insert_motifs2)]
|
||
|
|
insert_motifs2<-cbind("Num"=insert_motifs2, "Sample" = 1)
|
||
|
|
insert_motifs2<-data.frame(insert_motifs2)
|
||
|
|
for (i in samples) {
|
||
|
|
temp <- tp2[tp2$Sample==i,][,11]
|
||
|
|
temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
|
||
|
|
temp <- unlist(strsplit(temp,","))
|
||
|
|
temp<- temp[!numbers_only(temp)]
|
||
|
|
temp<-cbind("Num"=temp, "Sample" = i)
|
||
|
|
temp<-data.frame(temp)
|
||
|
|
insert_motifs2<-rbind(temp, insert_motifs2)
|
||
|
|
}
|
||
|
|
ggplot(insert_motifs2, aes(x = Num)) +
|
||
|
|
stat_count(geom='bar', width = 0.7, fill = "white", color = "black", alpha = 0.7) +
|
||
|
|
facet_wrap(~Sample, nrow=4, scales = "free_y") +
|
||
|
|
ggtitle("Insert motifs per sample") +
|
||
|
|
theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
|
||
|
|
ggsave("../report/images_read2/imps.png", width = 2250, height = 2500, units = "px")
|
||
|
|
rm (insert_motifs2, temp)
|
||
|
|
|
||
|
|
#Frequency of deletion motifs per sample
|
||
|
|
|
||
|
|
delete_motifs2 <- tp2[tp2$Sample==1,][,10]
|
||
|
|
delete_motifs2 <- unlist(strsplit(delete_motifs2, split="|",fixed = TRUE))
|
||
|
|
delete_motifs2 <- unlist(strsplit(delete_motifs2,","))
|
||
|
|
delete_motifs2<- delete_motifs2[!numbers_only(delete_motifs2)]
|
||
|
|
delete_motifs2<-cbind("Num"=delete_motifs2, "Sample" = 1)
|
||
|
|
delete_motifs2<-data.frame(delete_motifs2)
|
||
|
|
for (i in samples) {
|
||
|
|
temp <- tp2[tp2$Sample==i,][,10]
|
||
|
|
temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
|
||
|
|
temp <- unlist(strsplit(temp,","))
|
||
|
|
temp<- temp[!numbers_only(temp)]
|
||
|
|
temp<-cbind("Num"=temp, "Sample" = i)
|
||
|
|
temp<-data.frame(temp)
|
||
|
|
delete_motifs2<-rbind(temp, delete_motifs2)
|
||
|
|
}
|
||
|
|
ggplot(delete_motifs2, aes(x = Num)) +
|
||
|
|
stat_count(geom='bar', width = 0.7, fill = "white", color = "black", alpha = 0.7) +
|
||
|
|
facet_wrap(~Sample, nrow=4, scales = "free_y") +
|
||
|
|
ggtitle("Deletes motifs per sample") +
|
||
|
|
theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
|
||
|
|
ggsave("../report/images_read2/dmps.png", width = 2250, height = 2500, units = "px")
|
||
|
|
rm (delete_motifs2, temp)
|