227 lines
5.3 KiB
R
227 lines
5.3 KiB
R
getwd()
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setwd("~/git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts/plotting")
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getwd()
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########################################################################
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# Installing and loading required packages #
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########################################################################
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source("../Header_TT.R")
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#source("barplot_colour_function.R")
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require(data.table)
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########################################################################
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# Read file: call script for combining df #
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########################################################################
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source("../combining_two_df.R")
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#---------------------- PAY ATTENTION
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# the above changes the working dir
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#[1] "git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts"
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#---------------------- PAY ATTENTION
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#==========================
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# This will return:
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# df with NA:
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# merged_df2
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# merged_df3
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# df without NA:
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# merged_df2_comp
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# merged_df3_comp
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#==========================
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###########################
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# Data for plots
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# you need merged_df2, comprehensive one
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# since this has one-many relationship
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# i.e the same SNP can belong to multiple lineages
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###########################
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# uncomment as necessary
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#<<<<<<<<<<<<<<<<<<<<<<<<<
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# REASSIGNMENT
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my_df = merged_df2
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#my_df = merged_df2_comp
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#<<<<<<<<<<<<<<<<<<<<<<<<<
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# delete variables not required
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rm(merged_df2, merged_df2_comp, merged_df3, merged_df3_comp)
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# quick checks
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colnames(my_df)
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str(my_df)
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# Ensure correct data type in columns to plot: need to be factor
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is.factor(my_df$lineage)
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my_df$lineage = as.factor(my_df$lineage)
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is.factor(my_df$lineage)
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#==========================
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# Plot: Lineage barplot
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# x = lineage y = No. of samples
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# col = Lineage
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# fill = lineage
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#============================
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table(my_df$lineage)
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# lineage1 lineage2 lineage3 lineage4 lineage5 lineage6 lineageBOV
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#3 104 1293 264 1311 6 6 105
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#===========================
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# Plot: Lineage Barplots
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#===========================
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#===================
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# Data for plots
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#===================
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#<<<<<<<<<<<<<<<<<<<<<<<<<
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# REASSIGNMENT
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df <- my_df
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#<<<<<<<<<<<<<<<<<<<<<<<<<
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rm(my_df)
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# get freq count of positions so you can subset freq<1
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#setDT(df)[, lineage_count := .N, by = .(lineage)]
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#******************
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# generate plot: barplot of mutation by lineage
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#******************
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sel_lineages = c("lineage1"
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, "lineage2"
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, "lineage3"
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, "lineage4")
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df_lin = subset(df, subset = lineage %in% sel_lineages )
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#FIXME; add sanity check for numbers.
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# Done this manually
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############################################################
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#########
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# Data for barplot: Lineage barplot
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# to show total samples and number of unique mutations
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# within each linege
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##########
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# Create df with lineage inform & no. of unique mutations
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# per lineage and total samples within lineage
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# this is essentially barplot with two y axis
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bar = bar = as.data.frame(sel_lineages) #4, 1
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total_snps_u = NULL
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total_samples = NULL
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for (i in sel_lineages){
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#print(i)
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curr_total = length(unique(df$id)[df$lineage==i])
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total_samples = c(total_samples, curr_total)
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print(total_samples)
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foo = df[df$lineage==i,]
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print(paste0(i, "======="))
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print(length(unique(foo$Mutationinformation)))
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curr_count = length(unique(foo$Mutationinformation))
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total_snps_u = c(total_snps_u, curr_count)
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}
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print(total_snps_u)
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bar$num_snps_u = total_snps_u
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bar$total_samples = total_samples
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bar
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#*****************
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# generate plot: lineage barplot with two y-axis
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#https://stackoverflow.com/questions/13035295/overlay-bar-graphs-in-ggplot2
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#*****************
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bar$num_snps_u = y1
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bar$total_samples = y2
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sel_lineages = x
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to_plot = data.frame(x = x
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, y1 = y1
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, y2 = y2)
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to_plot
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melted = melt(to_plot, id = "x")
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melted
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# set output dir for plots
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getwd()
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setwd("~/git/Data/pyrazinamide/output/plots")
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getwd()
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svg('lineage_basic_barplot.svg')
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my_ats = 20 # axis text size
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my_als = 22 # axis label size
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g = ggplot(melted
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, aes(x = x
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, y = value
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, fill = variable)
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)
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printFile = g + geom_bar(
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#g + geom_bar(
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stat = "identity"
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, position = position_stack(reverse = TRUE)
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, alpha=.75
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, colour='grey75'
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) + theme(
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axis.text.x = element_text(
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size = my_ats
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# , angle= 30
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)
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, axis.text.y = element_text(size = my_ats
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#, angle = 30
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, hjust = 1
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, vjust = 0)
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, axis.title.x = element_text(
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size = my_als
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, colour = 'black'
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)
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, axis.title.y = element_text(
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size = my_als
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, colour = 'black'
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)
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, legend.position = "top"
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, legend.text = element_text(size = my_als)
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#) + geom_text(
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) + geom_label(
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aes(label = value)
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, size = 5
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, hjust = 0.5
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, vjust = 0.5
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, colour = 'black'
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, show.legend = FALSE
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#, check_overlap = TRUE
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, position = position_stack(reverse = T)
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#, position = ('
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) + labs(
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title = ''
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, x = ''
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, y = "Number"
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, fill = 'Variable'
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, colour = 'black'
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) + scale_fill_manual(
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values = c('grey50', 'gray75')
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, name=''
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, labels=c('Mutations', 'Total Samples')
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) + scale_x_discrete(
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breaks = c('lineage1', 'lineage2', 'lineage3', 'lineage4')
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, labels = c('Lineage 1', 'Lineage 2', 'Lineage 3', 'Lineage 4')
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)
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print(printFile)
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dev.off()
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