Reformat data for ggplot 2

Import Data and packages:

Packages:

library(ggplot2)
library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Data:

gene_coverage_18486_count= read.csv("../data/gene_cov_count/gene_coverage_18486_count.txt", header=FALSE, sep="\t")

gene_coverage_18508_dep_count= read.csv("../data/gene_cov_count/gene_coverage_18508_dep_count.txt", header=FALSE, sep="\t")

gene_coverage_18508_nondep_count= read.csv("../data/gene_cov_count/gene_coverage_18508_nondep_count.txt", header=FALSE, sep="\t")

gene_coverage_19238_dep_count= read.csv("../data/gene_cov_count/gene_coverage_19238_dep_count.txt", header=FALSE, sep="\t")

gene_coverage_mayer_dep_count = read.csv("../data/gene_cov_count/gene_coverage_mayer_SRR1575922_count.txt", header=FALSE, sep="\t")

Add col names:

colnames(gene_coverage_18486_count) = c("chr", "start", "end", "name", "score", "strand", "counts")
colnames(gene_coverage_18508_dep_count)= c("chr", "start", "end", "name", "score", "strand", "counts")
colnames(gene_coverage_18508_nondep_count)=c("chr", "start", "end", "name", "score", "strand", "counts")
colnames(gene_coverage_19238_dep_count)= c("chr", "start", "end", "name", "score", "strand", "counts")
colnames(gene_coverage_mayer_dep_count)= c("chr", "start", "end", "name", "score", "strand", "counts")

Reformat each file

Add a column to each file with the library using dplyr.

gene_coverage_18486_count= mutate(gene_coverage_18486_count, library="lib_18486")
gene_coverage_18508_dep_count= mutate(gene_coverage_18508_dep_count, library="lib_18508_dep")
gene_coverage_18508_nondep_count= mutate(gene_coverage_18508_nondep_count, library="lib_18508_nondep")
gene_coverage_19238_dep_count= mutate(gene_coverage_19238_dep_count, library="lib_19238")
gene_coverage_mayer_dep_count= mutate(gene_coverage_mayer_dep_count, library="lib_mayer")

Combine files

gene_cov_all_ggplot= bind_rows(gene_coverage_18486_count,gene_coverage_18508_dep_count,gene_coverage_18508_nondep_count,gene_coverage_19238_dep_count, gene_coverage_mayer_dep_count )

Make plots

Make a violin plot:

violin_plot_gene_counts= ggplot(gene_cov_all_ggplot, aes(library, counts/(end-start))) + geom_violin() + labs(x="Library", y="Gene count standardized by length", title="Standard gene count violin plots") 
violin_plot_gene_counts

Session information

sessionInfo()

R version 3.4.2 (2017-09-28)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] dplyr_0.7.4   ggplot2_2.2.1

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.13     bindr_0.1        knitr_1.17       magrittr_1.5    
 [5] munsell_0.4.3    colorspace_1.3-2 R6_2.2.2         rlang_0.1.4     
 [9] stringr_1.2.0    plyr_1.8.4       tools_3.4.2      grid_3.4.2      
[13] gtable_0.2.0     git2r_0.19.0     htmltools_0.3.6  yaml_2.1.14     
[17] lazyeval_0.2.1   rprojroot_1.2    digest_0.6.12    assertthat_0.2.0
[21] tibble_1.3.4     bindrcpp_0.2     glue_1.2.0       evaluate_0.10.1 
[25] rmarkdown_1.6    labeling_0.3     stringi_1.1.5    compiler_3.4.2  
[29] scales_0.5.0     backports_1.1.1  pkgconfig_2.0.1