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64 lines
2.6 KiB
R
64 lines
2.6 KiB
R
#Author, date: Elinor Sterner(esterner27@gmail.com), March 2023.
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#Motivation: To describe transcriptomes.
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#Intent: Plot length, coverage and GC of assembled transcripts with stats generated from assess_transcriptomes.py.
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#Dependencies: Python3
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#Inputs: assess_transcriptomes.py output (assembly_assessment.csv)
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#Outputs: Several plots showing the distribution of length, GC content, and Coverage.
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library(ggplot2)
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library(tidyverse)
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library(scales)
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#read in data output by python script
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transcriptome_data <- read.csv('assembly_assessment.csv')
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#make a column combining ten digit code and taxon information
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transcriptome_data_expert_level <- transcriptome_data|>
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mutate(taxon_id = paste(ten_digit_code, taxon_info, sep = "-"))
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#plot length vs coverage, faceted and labeled by taxon
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len_cov <- ggplot(transcriptome_data, aes(x = GC, y = length, color = taxon_info))+
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geom_point(size = .5)+
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ylim(200, 15000)+
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facet_wrap(~ten_digit_code + taxon_info)+
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ggtitle('GC% and length of Allogromia assembled transcripts')+
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theme(strip.text = element_text(size = 7))
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ggsave('len_cov.png', device = 'png', width = 8.5, height = 6)#save plot
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#plot distribution of GC
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dist_gc <- ggplot(transcriptome_data_expert_level, aes(x = GC, fill = taxon_info))+
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geom_histogram()+
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facet_wrap(~factor(taxon_id, levels = unique(taxon_id)))+# facet_grid(~factor(my_variable, levels=c('val1', 'val2', 'val3', ...)))
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ggtitle('Distribution of GC')+
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theme(strip.text = element_text(size = 5))
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dist_gc
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ggsave('gc_dist.png', device = 'png', width = 8, height = 6)
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#plot distribution of length
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dist_len <- ggplot(transcriptome_data_expert_level, aes(x = reorder(taxon_id,length), y = length, color = taxon_info, fill= taxon_info))+
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geom_violin()+
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geom_boxplot(color = 'Black', fill = 'NA', outlier.shape = NA, width = 0.5)+
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ggtitle('Length Distribution')+
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scale_y_continuous(labels = comma, trans = 'log10')+
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ylab('Length (log10)')+
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xlab('Ten digit code, taxon info')
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dist_len + theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))
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ggsave('length_violin.png', device = 'png',width = 7.5, height = 6)
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#plot distribution of coverage
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dist_cov <- ggplot(transcriptome_data_expert_level, aes(x = reorder(taxon_id,cov), y = cov, color = taxon_info, fill= taxon_info))+
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geom_violin()+
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geom_boxplot(color = 'Black', fill = 'NA', outlier.shape = NA, width = 0.5)+
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ggtitle('Distribution of coverage')+
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scale_y_continuous(labels = comma, trans = 'log10')+
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ylab('Coverage (log10)')+
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xlab('Ten digit code, taxon info')
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dist_cov+theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))
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ggsave('cov_violin.png', device = 'png', width = 7.5, height = 6)
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