Final version

chromosome.R

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+library(ggplot2)
+library(stringr)
+#####
+#This part of scripts produces the plots of alignment data. Only genome-aligned reverse reads were taken here. 
+#For every sample was created a set of reads of equal capacity (min between all sample reads).
+#####
+
+#Uploading data in R
+
+temp_name<-read.table("names_of_custom_genome.txt")
+samples_ecoli_chr <- c()
+for (i in temp_name[,c("V1")]) {
+  samples_ecoli_chr<-c(samples_ecoli_chr, gsub("_genome_mapq20_table.txt", "", gsub("custom_", "", i)))
+}
+tp2_genome <- data.frame(matrix(ncol = 24, nrow = 0))
+colnames(tp2_genome) <- unlist(strsplit("ID;Read;Count_SNPs;Cycles;GC;Mean_length_del;Mean_length_insert;Read_length;Align_length;Dels;Inserts;A>C;A>G;A>T;C>A;C>G;C>T;G>A;G>C;G>T;T>A;T>C;T>G",";"))
+for (i in temp_name[,c("V1")]) {
+  temp<-read.csv(i, sep=";", header=TRUE)
+  temp<-subset(temp, Read==2)
+  temp<-temp[sample(nrow(temp), 500000),]
+  temp<-cbind(temp, "Sample"=gsub("_genome_mapq20_table.txt", "", gsub("custom_", "", i)))
+  tp2_genome<-rbind(tp2_genome, temp)
+}
+rm(temp, temp_name)
+tp2_genome$Sample<-as.factor(tp2_genome$Sample)
+dir.create("../report/images_new_genome")
+
+#GC-content
+
+ggplot(data = tp2_genome, aes(x = GC)) +
+  geom_density(stat = "density", fill = "pink", alpha = 0.5) +
+  facet_wrap(~Sample, nrow = 3) +
+  geom_vline(xintercept = 50, linetype="dotted") + 
+  xlab("ГЦ-состав, %") +
+  ylab("Доля прочтений") +
+  xlim(25, 75) +
+  ylim(0, 0.15) +
+  theme(plot.title = element_text(hjust = 0.5))
+ggsave("../report/images_new_genome/gc.png", width = 2250, height = 1500, units = "px")
+
+#Mismatches per cycle of sequence
+
+df2<-data.frame(matrix(nrow = 0, ncol = 2))
+colnames(df2)<-c("Cycles", "Sample")
+for (i in samples_ecoli_chr) {
+  cyc <-subset(tp2_genome, Sample == i)[,4]
+  cyc <- as.numeric(unlist(strsplit(cyc,",")))
+  df2<-rbind(df2, cbind("Cycles" = cyc, "Sample" =i))
+}
+df2$Sample<-as.factor(df2$Sample)
+df2$Cycles<-as.numeric(df2$Cycles)
+rm (cyc, i)
+ggplot(df2, aes(x = Cycles)) +
+  geom_density(stat = "count", fill = "blue", alpha = 0.5) +
+  #geom_line(stat = "count", fill = "blue", alpha = 0.5) +
+  facet_wrap(~Sample, nrow = 3) +
+  xlab("Цикл прочтения, №")+
+  ylab("Количество замен")+
+  ggtitle("Количество однонуклеотидных замен по циклам") +
+  theme(plot.title = element_text(hjust = 0.5))
+ggsave("../report/images_new_genome/mpc.png", width = 2250, height = 1500, units = "px")
+ggplot(df2, aes(x = Cycles)) +
+  geom_density(stat = "density", fill = "blue", alpha = 0.5) +
+  facet_wrap(~Sample, nrow = 3) +
+  xlab("Цикл прочтения, №")+
+  ylab("Доля от общего количества")+
+  ggtitle("Количество однонуклеотидных замен по циклам") +
+  theme(plot.title = element_text(hjust = 0.5))
+ggsave("../report/images_new_genome/mpc_density.png", width = 2250, height = 1500, units = "px")
+rm (df2)
+
+#Mismatches depending on GC-content
+
+mgc2<-cbind(tp2_genome[, c("Count_SNPs", "Sample")], "GC" = round(tp2_genome$GC))
+ggplot(mgc2, aes(x=GC, y=Count_SNPs)) +
+  stat_summary(fun = sum, geom="line", linewidth = 0.5) +
+  facet_wrap(~Sample, nrow = 3) +
+  xlab("ГЦ-состав, %")+
+  ylab("Количество однонуклеотидных замен")+
+  ggtitle("Количество однонуклеотидных замен в зависимости от ГЦ-состава прочтений") +
+  geom_vline(xintercept = 50, linetype="dotted") + 
+  theme_bw()+
+  theme(plot.title = element_text(hjust = 0.5))
+ggsave("../report/images_new_genome/mgc.png", width = 2250, height = 1500, units = "px")
+ggplot(mgc2, aes(x=GC, y=Count_SNPs)) +
+  stat_summary(fun = mean, geom="line", size = 0.5) +
+  facet_wrap(~Sample, nrow = 3) +
+  xlab("ГЦ-состав, %")+
+  ylab("Среднее число однонуклеотидных замен на одно прочтение")+
+  ggtitle("Количество однонуклеотидных замен в зависимости от ГЦ-состава прочтения") +
+  geom_vline(xintercept = 50, linetype="dotted") + 
+  theme_bw()+
+  theme(plot.title = element_text(hjust = 0.5))
+ggsave("../report/images_new_genome/mgc_mean.png", width = 2250, height = 1500, units = "px")
+rm (mgc2)
+
+#Frequency of different types of mismatches
+
+mtype2 <- data.frame(matrix(ncol = 3, nrow = 0))
+colnames(mtype2)<- c("Sum", "type", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- apply(tp2_genome[, c(12:23)][tp2_genome$Sample==i,], 2, sum)
+  temp <- data.frame("Sum" = temp)
+  temp$type<-as.factor(colnames(tp2_genome[, c(12:23)]))
+  temp<-cbind(temp, "Sample" = i)
+  mtype2<-rbind(mtype2, temp)
+}
+ggplot(mtype2) +
+  geom_line(aes(x = type, y = Sum, group = Sample)) +
+  geom_point(aes(x = type, y = Sum)) +
+  #facet_wrap(~Sample, nrow = 3, scales = "free_y") +
+  facet_wrap(~Sample, nrow = 3, ) +
+  xlab("Тип однонуклеотидной замены")+
+  ylab("Количество однонуклеотидных замен")+
+  ggtitle("Частота типов однонуклеотидных замен") +
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/mt.png", width = 2250, height = 1500, units = "px")
+
+mtype2_2 <- data.frame(matrix(ncol = 3, nrow = 0))
+colnames(mtype2_2)<- c("mean", "type", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- apply(tp2_genome[tp2_genome$Sample==i, c(12:23)], 2, mean)
+  temp <- data.frame("mean" = temp)
+  temp$type<-as.factor(colnames(tp2_genome[, c(12:23)]))
+  temp<-cbind(temp, "Sample" = i)
+  mtype2_2<-rbind(mtype2_2, temp)
+}
+ggplot(mtype2_2) +
+  geom_line(aes(x = type, y = mean, group = Sample)) +
+  geom_point(aes(x = type, y = mean)) +
+  #facet_wrap(~Sample, nrow = 3, scales = "free_y") +
+  facet_wrap(~Sample, nrow = 3) +
+  xlab("Тип однонуклеотидной замены")+
+  ylab("Среднее по прочтению")+
+  ggtitle("Частота типов однонуклеотидных замен") +
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/mt_mean.png", width = 2250, height = 1500, units = "px")
+rm(mtype2, mtype2_2)
+
+#Number of deletions per sample
+
+delets2 <- data.frame(matrix(ncol = 2, nrow = 0))
+colnames(delets2)<- c("Nucleotide", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- tp2_genome[tp2_genome$Sample==i,][,10]
+  temp <- unlist(strsplit(temp,""))
+  temp<- temp[temp %in% c(letters, LETTERS)]
+  temp<-cbind("Nucleotide"=temp, "Sample" = i)
+  temp<-data.frame(temp)
+  temp$Nucleotide <- as.factor(temp$Nucleotide)
+  delets2<-rbind(temp, delets2)
+}
+ggplot(delets2) +
+  geom_bar(aes(x = Nucleotide), width = 0.4, fill = "blue", alpha = 0.5, col = "black") +
+  facet_wrap(~Sample, nrow = 3) +
+  #ylim(0, 1500) +
+  xlab("Нуклеотид")+
+  ylab("Количество делеций")+
+  ggtitle("Состав делеций") +
+  theme(plot.title = element_text(hjust = 0.5))
+ggsave("../report/images_new_genome/delets.png", width = 2250, height = 1500, units = "px")
+rm (delets2)
+
+#Number of insertions per sample
+
+inserts2 <- data.frame(matrix(ncol = 2, nrow = 0))
+colnames(inserts2)<- c("Nucleotide", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- tp2_genome[tp2_genome$Sample==i,][,11]
+  temp <- unlist(strsplit(temp,""))
+  temp<- temp[temp %in% c(letters, LETTERS)]
+  temp<-cbind("Nucleotide"=temp, "Sample" = i)
+  temp<-data.frame(temp)
+  temp$Nucleotide <- as.factor(temp$Nucleotide)
+  inserts2<-rbind(temp, inserts2)
+}
+ggplot(inserts2) +
+  xlab("Нуклеотид")+
+  ylab("Количество вставок")+
+  ggtitle("Состав вставок") +
+  geom_bar(aes(x = Nucleotide), width = 0.4, fill = "blue", alpha = 0.5, col = "black") +
+  facet_wrap(~Sample, nrow = 3) +
+  #ylim(0, 2000) +
+  theme(plot.title = element_text(hjust = 0.5))
+ggsave("../report/images_new_genome/inserts.png", width = 2250, height = 1500, units = "px")
+rm (inserts2)
+
+#Mean, min and max values of insertions per sample
+
+insert_mean2 <- data.frame(matrix(ncol = 7, nrow = 0))
+colnames(insert_mean2)<- c("Sample", "Min.", "1st Qu.", "Median", "Mean", "3rd Qu.", "Max.")
+for (i in samples_ecoli_chr) {
+  temp<-subset(tp2_genome, Mean_length_del!=0 & Sample == i)[,7]
+  temp<-cbind("Sample"=i, t(summary(temp)))
+  insert_mean2<-rbind(insert_mean2, temp)
+}
+insert_mean2[, 2]<-as.numeric(insert_mean2[, 2])
+insert_mean2[, 4]<-as.numeric(insert_mean2[, 4])
+insert_mean2[, 5]<-as.numeric(insert_mean2[, 5])
+insert_mean2[, 7]<-as.numeric(insert_mean2[, 7])
+ggplot(data.frame(insert_mean2), aes(x = factor(Sample), y = Mean), size = 0.5) +
+  geom_pointrange(aes(ymin = 0, ymax = Max.)) +
+  geom_point(aes(x = factor(Sample), y = 0), shape = 1) +
+  geom_point(aes(x = factor(Sample), y = Max.), shape = 1) +
+  xlab("Образец")+
+  ylab("Количество нуклеотидов")+
+  ggtitle("Статистика длины вставки") +
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/iml.png", width = 2250, height = 1500, units = "px")
+rm (insert_mean2)
+
+#Mean, min and max values of deletions per sample
+
+delete_mean2 <- data.frame(matrix(ncol = 7, nrow = 0))
+colnames(delete_mean2)<- c("Sample", "Min.", "1st Qu.", "Median", "Mean", "3rd Qu.", "Max.")
+for (i in samples_ecoli_chr) {
+  temp<-subset(tp2_genome, Mean_length_del!=0 & Sample == i)[,6]
+  temp<-cbind("Sample"=i, t(summary(temp)))
+  delete_mean2<-rbind(delete_mean2, temp)
+}
+delete_mean2[, 2]<-as.numeric(delete_mean2[, 2])
+delete_mean2[, 4]<-as.numeric(delete_mean2[, 4])
+delete_mean2[, 5]<-as.numeric(delete_mean2[, 5])
+delete_mean2[, 7]<-as.numeric(delete_mean2[, 7])
+ggplot(data.frame(delete_mean2), aes(x = factor(Sample), y = Mean), size = 0.5) +
+  geom_pointrange(aes(ymin = 0, ymax = Max.)) +
+  geom_point(aes(x = factor(Sample), y = 0), shape = 1) +
+  geom_point(aes(x = factor(Sample), y = Max.), shape = 1) +
+  xlab("Образец")+
+  ylab("Количество нуклеотидов")+
+  ggtitle("Статистика длины делеции") +
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/dml.png", width = 2250, height = 1500, units = "px")
+rm(delete_mean2)
+
+#Number of mismatches per sample
+
+ggplot(tp2_genome, aes(x=Sample, y=Count_SNPs, group = 1)) +
+  stat_summary(fun = sum, geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
+  xlab("Образец")+
+  ylab("Количество замен")+
+  ggtitle("Количество однонуклеотидных замен") +
+  #geom_vline(xintercept = 50, linetype="dotted") + 
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/mps_mean.png", width = 2250, height = 1500, units = "px")
+
+
+ggplot(tp2_genome, aes(x=Sample, y=Count_SNPs, group = 1)) +
+  stat_summary(fun = mean, geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
+  xlab("Образец")+
+  ylab("Среднее число замен")+
+  ggtitle("Количество однонуклеотидных замен на одно прочтение") +
+  #geom_vline(xintercept = 50, linetype="dotted") + 
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/mps.png", width = 2250, height = 1500, units = "px")
+
+#Number of deletions per cycle of sequence
+
+numbers_only <- function(x) !grepl("\\D", x)
+
+dels2 <- data.frame(matrix(nrow = 0, ncol = 2))
+colnames(dels2)<-c("Num", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- tp2_genome[tp2_genome$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)
+  dels2<-rbind(temp, dels2)
+}
+dels2$Num<-as.numeric(dels2$Num)
+ggplot(dels2, aes(x = Num)) +
+  #geom_density(stat = "count", alpha = 0.5) +
+  stat_count(geom="line", position="identity") +
+  stat_count(geom="point", position="identity", size = 1) +
+  facet_wrap(~Sample, nrow = 3) +
+  #ylim(0, 1500) +
+  xlab("Цикл прочтения, №")+
+  ylab("Количество делеций")+
+  ggtitle("Число делеций на цикл") +
+  theme_bw()+
+  theme(plot.title = element_text(hjust = 0.5))
+ggsave("../report/images_new_genome/dpc.png", width = 2250, height = 1500, units = "px")
+rm(dels2)
+
+#Number of insertions per cycle of sequence
+
+ins2 <- data.frame(matrix(nrow = 0, ncol = 2))
+colnames(ins2)<-c("Num", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- tp2_genome[tp2_genome$Sample==i,][,11]
+  temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
+  temp <- unlist(strsplit(temp,","))
+  temp<- temp[numbers_only(temp)]
+  temp<-cbind("Num"=temp, "Sample" = i)
+  temp<-data.frame(temp)
+  ins2<-rbind(temp, ins2)
+}
+ins2$Num<-as.numeric(ins2$Num)
+ggplot(ins2, aes(x = Num)) +
+  stat_count(geom="line", position="identity") +
+  stat_count(geom="point", position="identity", size = 1) +
+  facet_wrap(~Sample, nrow = 3) +
+  #ylim(0, 1500) +
+  xlab("Цикл прочтения, №")+
+  ylab("Количество вставок")+
+  ggtitle("Число вставок на цикл") +
+  scale_x_continuous(breaks=seq(0, 150, 25))+
+  theme_bw()+
+  theme(plot.title = element_text(hjust = 0.5)) 
+ggsave("../report/images_new_genome/ipc.png", width = 2250, height = 1500, units = "px")
+rm (ins2)
+
+#Number of deletions per sample
+
+parse_delets2 <- data.frame(matrix(nrow = 0, ncol = 2))
+colnames(parse_delets2)<-c("Num", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- tp2_genome[tp2_genome$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) +
+  xlab("Образец")+
+  ylab("Количество делеций")+
+  ggtitle("Число делеций на образец") +
+  #geom_vline(xintercept = 50, linetype="dotted") + 
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/dps.png", width = 2250, height = 1500, units = "px")
+rm (parse_delets2)
+
+#Number of insertions per sample
+
+parse_inserts2 <- data.frame(matrix(nrow = 0, ncol = 2))
+colnames(parse_inserts2)<-c("Num", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- tp2_genome[tp2_genome$Sample==i,][,11]
+  temp <- unlist(strsplit(temp,split="|",fixed = TRUE))
+  temp<-cbind("Num"=temp, "Sample" = i)
+  temp<-data.frame(temp)
+  parse_inserts2<-rbind(temp, parse_inserts2)
+}
+ggplot(parse_inserts2, aes(x=Sample, group = 1)) +
+  stat_count(geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
+  xlab("Образец")+
+  ylab("Количество вставок")+
+  ggtitle("Число вставок на образец") +
+  #geom_vline(xintercept = 50, linetype="dotted") + 
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/ips.png", width = 2250, height = 1500, units = "px")
+rm (parse_inserts2, temp)
+
+#Frequency of insertion motifs per sample
+
+insert_motifs2 <- data.frame(matrix(nrow = 0, ncol = 2))
+colnames(insert_motifs2)<-c("Num", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- tp2_genome[tp2_genome$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") +
+  xlab("Мотив")+
+  ylab("Количество")+
+  ggtitle("Представленность мотивов вставок в образцах") +
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/imps.png", width = 10550, height = 2500, units = "px")
+rm (insert_motifs2, temp)
+
+#Frequency of deletion motifs per sample
+
+delete_motifs2 <- data.frame(matrix(nrow = 0, ncol = 2))
+colnames(delete_motifs2)<-c("Num", "Sample")
+for (i in samples_ecoli_chr) {
+  temp <- tp2_genome[tp2_genome$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") +
+  xlab("Мотив")+
+  ylab("Количество")+
+  ggtitle("Представленность мотивов делеций в образцах") +
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
+ggsave("../report/images_new_genome/dmps.png", width = 10550, height = 2500, units = "px")
+rm (delete_motifs2, temp)

custom_lib_fastp_zvl_without_assembly.sh

@@ -0,0 +1,46 @@
+#!/bin/bash
+source /storage/data1/marmi/miniconda/installation/etc/profile.d/conda.sh
+conda activate marmi_methylome
+
+#перед каждым запуском заполнять эти пять переменных и path_to_sample
+input_file="libs_11_12_23.csv"
+cell="V350165701"
+path_to_run="/storage/data1/aug/V350165701_repair"
+goal_dir="custom_libs_E_Coli_Zvl"
+path_to_assembly="/storage/data1/marmi/dec_custom_libs"
+
+path_to_python="/storage/data1/marmi/trial_scripts/split_assembly.py"
+path_to_python_chr="/storage/data1/marmi/trial_scripts/chromosome.py"
+#выкидываем заголовок и заменяем пробелы на нижние подчеркивания
+cp $input_file source_csv.csv
+sed -i 's/ /_/g' source_csv.csv
+
+<source_csv.csv awk -v a_cell="${cell}" -F"," 'NR!=1{print $1 " " a_cell "_L0" $4 "_" $3 "_1.fq.gz" " " a_cell "_L0" $4 "_" $3 "_2.fq.gz" " " $2 " " $4}' >reads_fastp.txt
+rm source_csv.csv
+
+cat reads_fastp.txt | while read i || [[ -n $i ]];
+do
+dir=`echo $i| awk '{split($0, array); print array[1]}'`
+if [ "$dir" == "$goal_dir" ]; then
+    fn1=`echo $i| awk '{split($0, array); print array[2]}'`
+    fn2=`echo $i| awk '{split($0, array); print array[3]}'`
+    sample=`echo $i| awk '{split($0, array); print array[4]}'`
+    lane=`echo $i| awk '{split($0, array); print array[5]}'`
+    path_to_sample="/storage/data1/marmi/dec_custom_libs_repaired_${sample}"
+    mkdir ${path_to_sample}
+    mkdir ${path_to_sample}/qc_source_files
+    cd ${path_to_sample}/qc_source_files
+    read1="${path_to_run}/L0${lane}/${fn1}"
+    read2="${path_to_run}/L0${lane}/${fn2}"
+    fastp -e 30 -w 7 --in1 ${read1} --in2 ${read2} \
+        --out1 custom_${sample}_1.fastq.gz --out2 custom_${sample}_2.fastq.gz \
+        --unpaired1 custom_${sample}_u.fastq.gz --unpaired2 custom_${sample}_u.fastq.gz \
+        1>fastp_custom_${sample}_output.txt 2>fastp_custom_${sample}_err.txt
+fi
+done
+#НЕ УДАЛЯТЬ READS_FASTP.TXT
+
+conda deactivate
+conda activate marmi_telegram
+telegram-send "Work_custom_union_assembly first step ends at `date`."
+conda deactivate

custom_lib_union_align_zvl.sh

@@ -0,0 +1,61 @@
+#!/bin/bash
+source /storage/data1/marmi/miniconda/installation/etc/profile.d/conda.sh
+conda activate marmi_methylome
+#перед каждым запуском заполнять эти три переменных и path_to_sample
+path_to_assembly="/storage/data1/marmi/dec_custom_libs_zvl/unicycler_assembly_custom"
+goal_dir="custom_libs_E_Coli_Zvl"
+path_to_tables="/storage/data1/marmi/dec_custom_libs_zvl/info_tables_repaired"
+mkdir /storage/data1/marmi/dec_custom_libs_zvl
+path_to_python="/storage/data1/marmi/trial_scripts/info_pol_mapq_union.py"
+mkdir ${path_to_tables}
+touch ${path_to_tables}/names_of_custom_chromosome.txt
+touch ${path_to_tables}/names_of_custom_plasmid.txt
+cat reads_fastp.txt | while read i || [[ -n $i ]];
+do
+dir=`echo $i| awk '{split($0, array); print array[1]}'`
+if [ "$dir" == "$goal_dir" ]; then
+        sample=`echo $i| awk '{split($0, array); print array[4]}'`
+        path_to_sample="/storage/data1/marmi/dec_custom_libs_repaired_${sample}"
+        name_of_dir="union_${sample}"
+        mkdir ${path_to_sample}/${name_of_dir}
+        cd ${path_to_sample}/${name_of_dir}
+        bwa mem -t 7 ${path_to_assembly}/assembly.fasta ../qc_source_files/custom_${sample}_1.fastq.gz \
+                ../qc_source_files/custom_${sample}_2.fastq.gz >custom_${sample}_paired.sam \
+                2>bwa_mem_custom_${sample}_paired.log
+        bwa mem -t 7 ${path_to_assembly}/assembly.fasta ../qc_source_files/custom_${sample}_u.fastq.gz \
+                >custom_${sample}_unpaired.sam \
+                2>bwa_mem_custom_${sample}_unpaired.log
+        samtools view -Sb -o custom_${sample}_paired.bam custom_${sample}_paired.sam
+        samtools view -Sb -o custom_${sample}_unpaired.bam custom_${sample}_unpaired.sam
+        rm custom_${sample}_paired.sam
+        rm custom_${sample}_unpaired.sam
+        samtools sort -o custom_${sample}_paired_sorted.bam custom_${sample}_paired.bam
+        samtools sort -o custom_${sample}_unpaired_sorted.bam custom_${sample}_unpaired.bam
+        samtools merge -o custom_${sample}.bam \
+                custom_${sample}_paired_sorted.bam custom_${sample}_unpaired_sorted.bam
+        samtools index custom_${sample}.bam
+        rm custom_${sample}_paired_sorted.bam
+        rm custom_${sample}_unpaired_sorted.bam
+        rm custom_${sample}_paired.bam
+        rm custom_${sample}_unpaired.bam
+        touch custom_${sample}_genome.txt
+        touch custom_${sample}_plasmid.txt
+        cat ${path_to_assembly}/chromosome_genome.txt | while read j || [[ -n $j ]];
+        do
+                samtools view -F 4 custom_${sample}.bam $j | grep 'MD:Z' >> custom_${sample}_genome.txt
+        done
+        cat ${path_to_assembly}/chromosome_plasmid.txt | while read j || [[ -n $j ]];
+        do
+                samtools view -F 4 custom_${sample}.bam $j | grep 'MD:Z' >> custom_${sample}_plasmid.txt
+        done
+        python3 ${path_to_python} ${sample}_genome ${path_to_sample}/${name_of_dir}/ ${path_to_tables}/
+        python3 ${path_to_python} ${sample}_plasmid ${path_to_sample}/${name_of_dir}/ ${path_to_tables}/
+        echo "custom_${sample}_genome_mapq20_table.txt" >>${path_to_tables}/names_of_custom_chromosome.txt
+        echo "custom_${sample}_plasmid_mapq20_table.txt" >>${path_to_tables}/names_of_custom_plasmid.txt
+        
+fi
+done
+conda deactivate
+conda activate marmi_telegram
+telegram-send "Work_custom_union_align second step ends at `date`."
+conda deactivate

info_pol_mapq_union.py

@@ -0,0 +1,170 @@
+# -*- coding: utf-8 -*-
+
+import sys
+import re
+
+def GC(buf):
+  gc = buf.upper().count('G') + buf.upper().count('C')
+  all = buf.upper().count('A') + buf.upper().count('T') + gc
+  return (gc / all * 100)
+
+def len_align(buf):
+  """
+  нужно передавать CIGAR
+  """
+  let = re.split('[0-9]+', buf)
+  let.remove("")
+  num = re.split('[MIDSH]{1}', buf)
+  num.remove("")
+  num = list(map(int, num))
+  length = 0
+  length_read = 0
+  for i in range(len(let)):
+    if (let[i]=="M") or  (let[i]=="I"):
+      length+=num[i]
+      length_read+=num[i]
+    elif ((let[i]=="S") or  (let[i]=="H")):
+      length_read+=num[i]
+  return (length, length_read)
+
+def info (buf, arg = "I"):
+  """
+  Передавать CIGAR
+  """
+  let = re.split('[0-9]+', buf)
+  let.remove("")
+  num = re.split('[MIDSH]{1}', buf)
+  num.remove("")
+  num = list(map(int, num))
+  count = 0
+  for i in range(len(let)):
+    if (let[i]==arg):
+      count+=num[i]
+  return count
+
+def info_insert (buf):
+  """
+  Передавать CIGAR, возращает позиции инсерции, включая левый символ и не включая правый символ
+  """
+  let = re.split('[0-9]+', buf)
+  let.remove("")
+  num = re.split('[MIDSH]{1}', buf)
+  num.remove("")
+  num = list(map(int, num))
+  start = 0
+  intervals = []
+  for i in range(len(let)):
+    if (let[i]=="I"):
+      intervals.append([start, start+num[i]])
+    if (let[i]=="D") or (let[i]=="H"):
+      continue
+    start+=num[i]
+  return tuple(intervals)
+
+def removal (buf):
+  """
+  Передавать CIGAR, возращает позиции удаления, включая левый символ и не включая правый символ
+  """
+  let = re.split('[0-9]+', buf)
+  let.remove("")
+  num = re.split('[MIDSH]{1}', buf)
+  num.remove("")
+  num = list(map(int, num))
+  start = 0
+  intervals = []
+  for i in range(len(let)):
+    if (let[i]=="I") or (let[i]=="S"):
+      intervals.append([start, start+num[i]])
+    if (let[i]=="D") or (let[i]=="H"):
+      continue
+    start+=num[i]
+  return tuple(intervals)
+
+def type_snp_text (seq, buf, cigar):
+  positions_ins = info_insert(cigar)
+  inserts_text = ''
+  inserts = []
+  for i in positions_ins:
+    inserts.append((seq[i[0]:i[1]], i[0]))
+    inserts_text = inserts_text + str(seq[i[0]:i[1]]) + "," + str(i[0]) + '|'
+  inserts_text = inserts_text[:-1]
+  gc_per = GC(seq)
+  positions = removal(cigar)
+  for i in positions:
+    if (i[1]<(len(seq))):
+      seq = seq[:i[0]] + "_"*(i[1]-i[0]) + seq[i[1]:]
+    else:
+      seq = seq[:i[0]] + "_"*(i[1]-i[0])
+  seq = seq.replace("_", "")
+  buf = buf.replace("MD:Z:", "")
+  types = {"A>C":0, "A>G":0, "A>T":0, "C>A":0, "C>G":0, "C>T":0, "G>A":0, "G>C":0, "G>T":0, "T>A":0, "T>C":0, "T>G":0}
+  cycles_text = ''
+  dels_text = ''
+  cycles = []
+  dels = []
+  let = re.split('[0-9]+', buf)
+  let.pop(0)
+  num = re.split('[ATGC^]+', buf)
+  num = list(map(int, num))
+  iter = 0
+  for i in range(len(num)):
+    iter+=num[i]
+    if (let[i] == '') or (let[i] == '\n'):
+      continue
+    if (let[i][0] == '^'):
+      dels_text = dels_text + str(let[i][1:]) + "," + str(iter) + "|"
+      dels.append((let[i][1:], iter))
+      continue
+    if (seq[iter]=="A") or (seq[iter]=="C") or (seq[iter]=="G") or (seq[iter]=="T"):
+      key = let[i] + ">" + seq[iter]
+      types[key]+=1
+      cycles.append(iter)
+      cycles_text = cycles_text + str(iter) + ","
+      iter+=1
+    else:
+      iter+=1
+  l = len_align(cigar)
+  dels_text = dels_text[:-1]
+  cycles_text = cycles_text[:-1]
+  if len(dels)!=0:
+    len_del = sum([len(dels[i][0]) for i in range(len(dels))])/len(dels)
+  else:
+    len_del = 0
+  if len(inserts)!=0:
+    len_ins = sum([len(inserts[i][0]) for i in range(len(inserts))])/len(inserts)
+  else:
+    len_ins = 0
+  result = {"SNP": types, "Cycles": cycles_text, "Dels": dels_text, "Inserts" : inserts_text, "GC": gc_per, "Count_SNPs": sum(types.values()), "Mean_length_del": len_del, \
+            "Mean_length_insert": len_ins, "Read_length": l[1], "Align_length": l[0]}
+  return result
+
+
+
+with open(sys.argv[3]+"custom_"+sys.argv[1]+"_mapq20_table.txt", 'w') as table:
+  header = "ID;Read;Count_SNPs;Cycles;GC;Mean_length_del;Mean_length_insert;Read_length;Align_length;Dels;Inserts;A>C;A>G;A>T;C>A;C>G;C>T;G>A;G>C;G>T;T>A;T>C;T>G\n"
+  table.write(header)
+  with open(sys.argv[2]+"custom_"+sys.argv[1]+".txt", 'r') as inp:
+    for line in inp:
+      columns = line.split("\t")
+      if int(columns[4])>20:
+        id = columns[0]
+        flag = columns[1]
+        binary = "{0:b}".format(int(flag))
+        if (binary[-1]=='0'):
+          typ = 0
+        elif len(binary)==7:
+          typ = 1
+        elif len(binary)>=8:
+          if (binary[-7]=='0') and (binary[-8]=='1'):
+            typ = 2
+          else:
+            typ = -1
+        else:
+          typ = -1
+        cigar = columns[5]
+        md = columns[12]
+        seq = columns[9]
+        inf = type_snp_text(seq, md, cigar)
+        stroke = id + ";" + str(typ) + ";" + str(inf['Count_SNPs']) + ";" + inf['Cycles'] + ";" + str(inf['GC']) + ";" + str(inf['Mean_length_del']) + ";" + str(inf['Mean_length_insert']) + ";" + str(inf['Read_length']) + ";" + str(inf['Align_length']) + ";" + inf['Dels'] + ";" + inf['Inserts'] + ";" + \
+        str(inf['SNP']['A>C']) + ";" + str(inf['SNP']['A>G']) + ";" + str(inf['SNP']['A>T']) + ";" + str(inf['SNP']['C>A']) + ";" + str(inf['SNP']['C>G']) + ";" + str(inf['SNP']['C>T']) + ";" + str(inf['SNP']['G>A']) + ";" + str(inf['SNP']['G>C']) + ";" + str(inf['SNP']['G>T']) + ";" + str(inf['SNP']['T>A']) + ";" + str(inf['SNP']['T>C']) + ";" + str(inf['SNP']['T>G']) + '\n'
+        table.write(stroke)

plasmid.R

@@ -8,29 +8,31 @@ library(stringr)
 #Uploading data in R
 
 temp_name<-read.table("names_of_custom_plasmid.txt")
-samples <- c()
+samples_ecoli <- c()
 for (i in temp_name[,c("V1")]) {
-  samples<-c(samples, gsub("_plasmid_mapq20_table.txt", "", gsub("custom_", "", i)))
+  samples_ecoli<-c(samples_ecoli, gsub("_plasmid_mapq20_table.txt", "", gsub("custom_", "", i)))
 }
-tp2 <- data.frame(matrix(ncol = 24, nrow = 0))
+tp2_plasmid <- data.frame(matrix(ncol = 24, nrow = 0))
-colnames(tp2) <- unlist(strsplit("ID;Read;Count_SNPs;Cycles;GC;Mean_length_del;Mean_length_insert;Read_length;Align_length;Dels;Inserts;A>C;A>G;A>T;C>A;C>G;C>T;G>A;G>C;G>T;T>A;T>C;T>G",";"))
+colnames(tp2_plasmid) <- unlist(strsplit("ID;Read;Count_SNPs;Cycles;GC;Mean_length_del;Mean_length_insert;Read_length;Align_length;Dels;Inserts;A>C;A>G;A>T;C>A;C>G;C>T;G>A;G>C;G>T;T>A;T>C;T>G",";"))
 for (i in temp_name[,c("V1")]) {
   temp<-read.csv(i, sep=";", header=TRUE)
   temp<-subset(temp, Read==2)
-  temp<-temp[sample(nrow(temp), 200000),]
+  temp<-temp[sample(nrow(temp), 100000),]
   temp<-cbind(temp, "Sample"=gsub("_plasmid_mapq20_table.txt", "", gsub("custom_", "", i)))
-  tp2<-rbind(tp2, temp)
+  tp2_plasmid<-rbind(tp2_plasmid, temp)
 }
 rm(temp, temp_name)
-tp2$Sample<-as.factor(tp2$Sample)
+tp2_plasmid$Sample<-as.factor(tp2_plasmid$Sample)
 dir.create("../report/images_new_plasmid")
 
 #GC-content
 
-ggplot(data = tp2, aes(x = GC)) +
+ggplot(data = tp2_plasmid, aes(x = GC)) +
   geom_density(stat = "density", fill = "pink", alpha = 0.5) +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
   geom_vline(xintercept = 50, linetype="dotted") + 
+  xlab("ГЦ-состав, %") +
+  ylab("Доля прочтений") +
   xlim(25, 75) +
   ylim(0, 0.15) +
   theme(plot.title = element_text(hjust = 0.5))
@@ -40,8 +42,8 @@ ggsave("../report/images_new_plasmid/gc.png", width = 2250, height = 1500, units
 
 df2<-data.frame(matrix(nrow = 0, ncol = 2))
 colnames(df2)<-c("Cycles", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  cyc <-subset(tp2, Sample == i)[,4]
+  cyc <-subset(tp2_plasmid, Sample == i)[,4]
   cyc <- as.numeric(unlist(strsplit(cyc,",")))
   df2<-rbind(df2, cbind("Cycles" = cyc, "Sample" =i))
 }
@@ -51,33 +53,41 @@ rm (cyc, i)
 ggplot(df2, aes(x = Cycles)) +
   geom_density(stat = "count", fill = "blue", alpha = 0.5) +
   #geom_line(stat = "count", fill = "blue", alpha = 0.5) +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
-  ggtitle("Mismatches per cycle") +
+  xlab("Цикл прочтения, №")+
+  ylab("Количество замен")+
+  ggtitle("Количество однонуклеотидных замен по циклам") +
   theme(plot.title = element_text(hjust = 0.5))
 ggsave("../report/images_new_plasmid/mpc.png", width = 2250, height = 1500, units = "px")
 ggplot(df2, aes(x = Cycles)) +
   geom_density(stat = "density", fill = "blue", alpha = 0.5) +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
-  ggtitle("Mismatches per cycle") +
+  xlab("Цикл прочтения, №")+
+  ylab("Доля от общего количества")+
+  ggtitle("Количество однонуклеотидных замен по циклам") +
   theme(plot.title = element_text(hjust = 0.5))
 ggsave("../report/images_new_plasmid/mpc_density.png", width = 2250, height = 1500, units = "px")
 rm (df2)
 
 #Mismatches depending on GC-content
 
-mgc2<-cbind(tp2[, c("Count_SNPs", "Sample")], "GC" = round(tp2$GC))
+mgc2<-cbind(tp2_plasmid[, c("Count_SNPs", "Sample")], "GC" = round(tp2_plasmid$GC))
 ggplot(mgc2, aes(x=GC, y=Count_SNPs)) +
   stat_summary(fun = sum, geom="line", linewidth = 0.5) +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
-  ggtitle("Mismatches/GC") +
+  xlab("ГЦ-состав, %")+
+  ylab("Количество однонуклеотидных замен")+
+  ggtitle("Количество однонуклеотидных замен в зависимости от ГЦ-состава прочтений") +
   geom_vline(xintercept = 50, linetype="dotted") + 
   theme_bw()+
   theme(plot.title = element_text(hjust = 0.5))
 ggsave("../report/images_new_plasmid/mgc.png", width = 2250, height = 1500, units = "px")
 ggplot(mgc2, aes(x=GC, y=Count_SNPs)) +
   stat_summary(fun = mean, geom="line", size = 0.5) +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
-  ggtitle("Mismatches/GC") +
+  xlab("ГЦ-состав, %")+
+  ylab("Среднее число однонуклеотидных замен на одно прочтение")+
+  ggtitle("Количество однонуклеотидных замен в зависимости от ГЦ-состава прочтения") +
   geom_vline(xintercept = 50, linetype="dotted") + 
   theme_bw()+
   theme(plot.title = element_text(hjust = 0.5))
@@ -88,37 +98,41 @@ rm (mgc2)
 
 mtype2 <- data.frame(matrix(ncol = 3, nrow = 0))
 colnames(mtype2)<- c("Sum", "type", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- apply(tp2[, c(12:23)][tp2$Sample==i,], 2, sum)
+  temp <- apply(tp2_plasmid[, c(12:23)][tp2_plasmid$Sample==i,], 2, sum)
   temp <- data.frame("Sum" = temp)
-  temp$type<-as.factor(colnames(tp2[, c(12:23)]))
+  temp$type<-as.factor(colnames(tp2_plasmid[, c(12:23)]))
   temp<-cbind(temp, "Sample" = i)
   mtype2<-rbind(mtype2, temp)
 }
 ggplot(mtype2) +
   geom_line(aes(x = type, y = Sum, group = Sample)) +
   geom_point(aes(x = type, y = Sum)) +
-  #facet_wrap(~Sample, nrow = 2, scales = "free_y") +
+  #facet_wrap(~Sample, nrow = 3, scales = "free_y") +
-  facet_wrap(~Sample, nrow = 2, ) +
+  facet_wrap(~Sample, nrow = 3, ) +
-  ggtitle("Mismatch type") +
+  xlab("Тип однонуклеотидной замены")+
+  ylab("Количество однонуклеотидных замен")+
+  ggtitle("Частота типов однонуклеотидных замен") +
   theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
 ggsave("../report/images_new_plasmid/mt.png", width = 2250, height = 1500, units = "px")
 
 mtype2_2 <- data.frame(matrix(ncol = 3, nrow = 0))
 colnames(mtype2_2)<- c("mean", "type", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- apply(tp2[tp2$Sample==i, c(12:23)], 2, mean)
+  temp <- apply(tp2_plasmid[tp2_plasmid$Sample==i, c(12:23)], 2, mean)
   temp <- data.frame("mean" = temp)
-  temp$type<-as.factor(colnames(tp2[, c(12:23)]))
+  temp$type<-as.factor(colnames(tp2_plasmid[, c(12:23)]))
   temp<-cbind(temp, "Sample" = i)
   mtype2_2<-rbind(mtype2_2, temp)
 }
 ggplot(mtype2_2) +
   geom_line(aes(x = type, y = mean, group = Sample)) +
   geom_point(aes(x = type, y = mean)) +
-  #facet_wrap(~Sample, nrow = 2, scales = "free_y") +
+  #facet_wrap(~Sample, nrow = 3, scales = "free_y") +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
-  ggtitle("Mismatch type") +
+  xlab("Тип однонуклеотидной замены")+
+  ylab("Среднее по прочтению")+
+  ggtitle("Частота типов однонуклеотидных замен") +
   theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
 ggsave("../report/images_new_plasmid/mt_mean.png", width = 2250, height = 1500, units = "px")
 rm(mtype2, mtype2_2)
@@ -127,8 +141,8 @@ rm(mtype2, mtype2_2)
 
 delets2 <- data.frame(matrix(ncol = 2, nrow = 0))
 colnames(delets2)<- c("Nucleotide", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- tp2[tp2$Sample==i,][,10]
+  temp <- tp2_plasmid[tp2_plasmid$Sample==i,][,10]
   temp <- unlist(strsplit(temp,""))
   temp<- temp[temp %in% c(letters, LETTERS)]
   temp<-cbind("Nucleotide"=temp, "Sample" = i)
@@ -138,9 +152,11 @@ for (i in samples) {
 }
 ggplot(delets2) +
   geom_bar(aes(x = Nucleotide), width = 0.4, fill = "blue", alpha = 0.5, col = "black") +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
   #ylim(0, 1500) +
-  ggtitle ("Deletions") +
+  xlab("Нуклеотид")+
+  ylab("Количество делеций")+
+  ggtitle("Состав делеций") +
   theme(plot.title = element_text(hjust = 0.5))
 ggsave("../report/images_new_plasmid/delets.png", width = 2250, height = 1500, units = "px")
 rm (delets2)
@@ -149,8 +165,8 @@ rm (delets2)
 
 inserts2 <- data.frame(matrix(ncol = 2, nrow = 0))
 colnames(inserts2)<- c("Nucleotide", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- tp2[tp2$Sample==i,][,11]
+  temp <- tp2_plasmid[tp2_plasmid$Sample==i,][,11]
   temp <- unlist(strsplit(temp,""))
   temp<- temp[temp %in% c(letters, LETTERS)]
   temp<-cbind("Nucleotide"=temp, "Sample" = i)
@@ -159,9 +175,11 @@ for (i in samples) {
   inserts2<-rbind(temp, inserts2)
 }
 ggplot(inserts2) +
-  ggtitle("Insertions") +
+  xlab("Нуклеотид")+
+  ylab("Количество вставок")+
+  ggtitle("Состав вставок") +
   geom_bar(aes(x = Nucleotide), width = 0.4, fill = "blue", alpha = 0.5, col = "black") +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
   #ylim(0, 2000) +
   theme(plot.title = element_text(hjust = 0.5))
 ggsave("../report/images_new_plasmid/inserts.png", width = 2250, height = 1500, units = "px")
@@ -171,8 +189,8 @@ rm (inserts2)
 
 insert_mean2 <- data.frame(matrix(ncol = 7, nrow = 0))
 colnames(insert_mean2)<- c("Sample", "Min.", "1st Qu.", "Median", "Mean", "3rd Qu.", "Max.")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp<-subset(tp2, Mean_length_del!=0 & Sample == i)[,7]
+  temp<-subset(tp2_plasmid, Mean_length_del!=0 & Sample == i)[,7]
   temp<-cbind("Sample"=i, t(summary(temp)))
   insert_mean2<-rbind(insert_mean2, temp)
 }
@@ -182,12 +200,12 @@ insert_mean2[, 5]<-as.numeric(insert_mean2[, 5])
 insert_mean2[, 7]<-as.numeric(insert_mean2[, 7])
 ggplot(data.frame(insert_mean2), aes(x = factor(Sample), y = Mean), size = 0.5) +
   geom_pointrange(aes(ymin = 0, ymax = Max.)) +
-  scale_y_continuous(name = "Length") +
   geom_point(aes(x = factor(Sample), y = 0), shape = 1) +
   geom_point(aes(x = factor(Sample), y = Max.), shape = 1) +
-  ggtitle("Insertion mean length") +
+  xlab("Образец")+
-  scale_x_discrete(name = "Sample") +
+  ylab("Количество нуклеотидов")+
-  theme(plot.title = element_text(hjust = 0.5))
+  ggtitle("Статистика длины вставки") +
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
 ggsave("../report/images_new_plasmid/iml.png", width = 2250, height = 1500, units = "px")
 rm (insert_mean2)
 
@@ -195,8 +213,8 @@ rm (insert_mean2)
 
 delete_mean2 <- data.frame(matrix(ncol = 7, nrow = 0))
 colnames(delete_mean2)<- c("Sample", "Min.", "1st Qu.", "Median", "Mean", "3rd Qu.", "Max.")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp<-subset(tp2, Mean_length_del!=0 & Sample == i)[,6]
+  temp<-subset(tp2_plasmid, Mean_length_del!=0 & Sample == i)[,6]
   temp<-cbind("Sample"=i, t(summary(temp)))
   delete_mean2<-rbind(delete_mean2, temp)
 }
@@ -208,29 +226,32 @@ ggplot(data.frame(delete_mean2), aes(x = factor(Sample), y = Mean), size = 0.5)
   geom_pointrange(aes(ymin = 0, ymax = Max.)) +
   geom_point(aes(x = factor(Sample), y = 0), shape = 1) +
   geom_point(aes(x = factor(Sample), y = Max.), shape = 1) +
-  ggtitle("Deletion mean length") +
+  xlab("Образец")+
-  scale_x_discrete(name = "Sample") +
+  ylab("Количество нуклеотидов")+
-  scale_y_continuous(name = "Length") +
+  ggtitle("Статистика длины делеции") +
-  theme(plot.title = element_text(hjust = 0.5))
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
 ggsave("../report/images_new_plasmid/dml.png", width = 2250, height = 1500, units = "px")
 rm(delete_mean2)
 
 #Number of mismatches per sample
 
-ggplot(tp2, aes(x=Sample, y=Count_SNPs, group = 1)) +
+ggplot(tp2_plasmid, aes(x=Sample, y=Count_SNPs, group = 1)) +
   stat_summary(fun = sum, geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
-  ggtitle("Mismatches per sample") +
+  xlab("Образец")+
+  ylab("Количество замен")+
+  ggtitle("Количество однонуклеотидных замен") +
   #geom_vline(xintercept = 50, linetype="dotted") + 
-  theme(plot.title = element_text(hjust = 0.5))
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
 ggsave("../report/images_new_plasmid/mps_mean.png", width = 2250, height = 1500, units = "px")
 
 
-ggplot(tp2, aes(x=Sample, y=Count_SNPs, group = 1)) +
+ggplot(tp2_plasmid, aes(x=Sample, y=Count_SNPs, group = 1)) +
-  stat_summary(fun = mean, geom="point") +
+  stat_summary(fun = mean, geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
-  stat_summary(fun = mean, geom="line") +
+  xlab("Образец")+
-  ggtitle("Mismatches per sample") +
+  ylab("Среднее число замен")+
+  ggtitle("Количество однонуклеотидных замен на одно прочтение") +
   #geom_vline(xintercept = 50, linetype="dotted") + 
-  theme(plot.title = element_text(hjust = 0.5))
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
 ggsave("../report/images_new_plasmid/mps.png", width = 2250, height = 1500, units = "px")
 
 #Number of deletions per cycle of sequence
@@ -239,8 +260,8 @@ numbers_only <- function(x) !grepl("\\D", x)
 
 dels2 <- data.frame(matrix(nrow = 0, ncol = 2))
 colnames(dels2)<-c("Num", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- tp2[tp2$Sample==i,][,10]
+  temp <- tp2_plasmid[tp2_plasmid$Sample==i,][,10]
   temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
   temp <- unlist(strsplit(temp,","))
   temp<- temp[numbers_only(temp)]
@@ -253,9 +274,11 @@ ggplot(dels2, aes(x = Num)) +
   #geom_density(stat = "count", alpha = 0.5) +
   stat_count(geom="line", position="identity") +
   stat_count(geom="point", position="identity", size = 1) +
-  facet_wrap(~Sample, nrow = 2) +
+  facet_wrap(~Sample, nrow = 3) +
   #ylim(0, 1500) +
-  ggtitle ("Deletions per cycle") +
+  xlab("Цикл прочтения, №")+
+  ylab("Количество делеций")+
+  ggtitle("Число делеций на цикл") +
   theme_bw()+
   theme(plot.title = element_text(hjust = 0.5))
 ggsave("../report/images_new_plasmid/dpc.png", width = 2250, height = 1500, units = "px")
@@ -265,8 +288,8 @@ rm(dels2)
 
 ins2 <- data.frame(matrix(nrow = 0, ncol = 2))
 colnames(ins2)<-c("Num", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- tp2[tp2$Sample==i,][,11]
+  temp <- tp2_plasmid[tp2_plasmid$Sample==i,][,11]
   temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
   temp <- unlist(strsplit(temp,","))
   temp<- temp[numbers_only(temp)]
@@ -278,9 +301,11 @@ 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 = 2, scales = "free_y") +
+  facet_wrap(~Sample, nrow = 3) +
   #ylim(0, 1500) +
-  ggtitle ("Insertions per cycle") +
+  xlab("Цикл прочтения, №")+
+  ylab("Количество вставок")+
+  ggtitle("Число вставок на цикл") +
   scale_x_continuous(breaks=seq(0, 150, 25))+
   theme_bw()+
   theme(plot.title = element_text(hjust = 0.5)) 
@@ -291,8 +316,8 @@ rm (ins2)
 
 parse_delets2 <- data.frame(matrix(nrow = 0, ncol = 2))
 colnames(parse_delets2)<-c("Num", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- tp2[tp2$Sample==i,][,10]
+  temp <- tp2_plasmid[tp2_plasmid$Sample==i,][,10]
   temp <- unlist(strsplit(temp,split="|",fixed = TRUE))
   temp<-cbind("Num"=temp, "Sample" = i)
   temp<-data.frame(temp)
@@ -300,9 +325,11 @@ for (i in samples) {
 }
 ggplot(parse_delets2, aes(x=Sample, group = 1)) +
   stat_count(geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
-  ggtitle("Deletions per sample") +
+  xlab("Образец")+
+  ylab("Количество делеций")+
+  ggtitle("Число делеций на образец") +
   #geom_vline(xintercept = 50, linetype="dotted") + 
-  theme(plot.title = element_text(hjust = 0.5))
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
 ggsave("../report/images_new_plasmid/dps.png", width = 2250, height = 1500, units = "px")
 rm (parse_delets2)
 
@@ -310,8 +337,8 @@ rm (parse_delets2)
 
 parse_inserts2 <- data.frame(matrix(nrow = 0, ncol = 2))
 colnames(parse_inserts2)<-c("Num", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- tp2[tp2$Sample==i,][,11]
+  temp <- tp2_plasmid[tp2_plasmid$Sample==i,][,11]
   temp <- unlist(strsplit(temp,split="|",fixed = TRUE))
   temp<-cbind("Num"=temp, "Sample" = i)
   temp<-data.frame(temp)
@@ -319,9 +346,11 @@ for (i in samples) {
 }
 ggplot(parse_inserts2, aes(x=Sample, group = 1)) +
   stat_count(geom="bar", width = 0.7, fill = "white", color = "black", alpha = 0.7) +
-  ggtitle("Insertions per sample") +
+  xlab("Образец")+
+  ylab("Количество вставок")+
+  ggtitle("Число вставок на образец") +
   #geom_vline(xintercept = 50, linetype="dotted") + 
-  theme(plot.title = element_text(hjust = 0.5))
+  theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
 ggsave("../report/images_new_plasmid/ips.png", width = 2250, height = 1500, units = "px")
 rm (parse_inserts2, temp)
 
@@ -329,8 +358,8 @@ rm (parse_inserts2, temp)
 
 insert_motifs2 <- data.frame(matrix(nrow = 0, ncol = 2))
 colnames(insert_motifs2)<-c("Num", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- tp2[tp2$Sample==i,][,11]
+  temp <- tp2_plasmid[tp2_plasmid$Sample==i,][,11]
   temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
   temp <- unlist(strsplit(temp,","))
   temp<- temp[!numbers_only(temp)]
@@ -341,17 +370,19 @@ for (i in samples) {
 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("Insertion motifs per sample") +
+  xlab("Мотив")+
+  ylab("Количество")+
+  ggtitle("Представленность мотивов вставок в образцах") +
   theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
-ggsave("../report/images_new_plasmid/imps.png", width = 3250, height = 2500, units = "px")
+ggsave("../report/images_new_plasmid/imps.png", width = 7550, height = 2500, units = "px")
 rm (insert_motifs2, temp)
 
 #Frequency of deletion motifs per sample
 
 delete_motifs2 <- data.frame(matrix(nrow = 0, ncol = 2))
 colnames(delete_motifs2)<-c("Num", "Sample")
-for (i in samples) {
+for (i in samples_ecoli) {
-  temp <- tp2[tp2$Sample==i,][,10]
+  temp <- tp2_plasmid[tp2_plasmid$Sample==i,][,10]
   temp <- unlist(strsplit(temp, split="|",fixed = TRUE))
   temp <- unlist(strsplit(temp,","))
   temp<- temp[!numbers_only(temp)]
@@ -362,7 +393,9 @@ for (i in samples) {
 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("Deletions motifs per sample") +
+  xlab("Мотив")+
+  ylab("Количество")+
+  ggtitle("Представленность мотивов делеций в образцах") +
   theme(plot.title = element_text(hjust = 0.5),axis.text.x = element_text(angle = 90, hjust = 1))
-ggsave("../report/images_new_plasmid/dmps.png", width = 4550, height = 2500, units = "px")
+ggsave("../report/images_new_plasmid/dmps.png", width = 7550, height = 2500, units = "px")
 rm (delete_motifs2, temp)