Example facet boxplots

Last updated: 2019-04-15

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File	Version	Author	Date	Message
Rmd	44b0544	brimittleman	2019-04-15	add facet bp examples

Yoav did not understand the heatmap plots. I want to try another mothod to demonstrate QTLs. I will use blox plots faceted by peak in the gene.

library(tidyverse)

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✔ readr   1.3.1       ✔ forcats 0.4.0

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library(reshape2)


Attaching package: 'reshape2'

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library(cowplot)

Warning: package 'cowplot' was built under R version 3.5.2


Attaching package: 'cowplot'

The following object is masked from 'package:ggplot2':

    ggsave

phenohead=read.table("../data/ExampleQTLplot2/Phenotypeheader.txt", header = T,stringsAsFactors = F)
phenoEIF=read.table("../data/ExampleQTLplot2/EIF2a_TotalPeaksPheno.txt", col.names =colnames(phenohead),stringsAsFactors = F)


meltpheno=melt(phenoEIF, id.vars = "chrom", value.name = "Ratio", variable.name = "Individual") %>% separate(Ratio, into=c("num", "denom"), sep="/") %>%   separate(chrom, into=c("chrom", "start", "end", "peakID"),sep=":") %>% mutate(PeakLoc=paste(start, end, sep=":"))


meltpheno$Individual= as.character(meltpheno$Individual)
meltpheno$num= as.numeric(meltpheno$num)
meltpheno$denom=as.numeric(meltpheno$denom)

genoHead=read.table("../data/ExampleQTLplot2/genotypeHeader.txt", header = T,stringsAsFactors = F)
genoEIF=read.table("../data/ExampleQTLplot2/EIF2a_TotalPeaksGenotype.txt", col.names =colnames(genoHead),stringsAsFactors = F ) %>% select(ID,contains("NA")) 

lettersGeno=read.table("../data/ExampleQTLplot2/EIF2a_TotalPeaksGenotype.txt", col.names =colnames(genoHead),stringsAsFactors = F, colClasses = c("character") ) %>% select(REF, ALT)



refAllele=as.character(lettersGeno$REF)
altAllele=as.character(lettersGeno$ALT)

genoMelt=melt(genoEIF, id.vars = "ID", value.name = "FullGeno", variable.name = "Individual" ) %>% separate(FullGeno, into=c("geno","dose","extra1"), sep=":") %>% select(Individual, dose) %>% mutate(genotype=ifelse(round(as.integer(dose))==0, paste(refAllele, refAllele, sep=""), ifelse(round(as.integer(dose))==1, paste(refAllele,altAllele, sep=""), paste(altAllele,altAllele,sep=""))))
genoMelt$Individual= as.character(genoMelt$Individual)

Join these by individual:

PhenandGene= meltpheno %>% inner_join(genoMelt, by="Individual") %>%  mutate(PAU=num/denom)

eif_facetBP=ggplot(PhenandGene, aes(x=genotype, y=PAU, fill=genotype)) + geom_boxplot(width=.5)+ geom_jitter(alpha=1) + facet_grid(~PeakLoc) +scale_fill_brewer(palette = "YlOrRd")
                                                                                                                        eif_facetBP

ggsave(eif_facetBP, file="../data/ExampleQTLplot2/eif_facetBPexample.png", height = 7, width = 12)

Try this verticle:

eif_facetBP_vert=ggplot(PhenandGene, aes(x=genotype, y=PAU, fill=genotype)) + geom_boxplot(width=.5)+ geom_jitter(alpha=1) + facet_wrap(~PeakLoc, ncol=1) +scale_fill_brewer(palette = "YlOrRd")

ggsave(eif_facetBP_vert, file="../data/ExampleQTLplot2/eif_facetBPexampleVERT.png", height = 20, width = 7)

Make this a reproduciple plot:

apaqtlfacetboxplots.R

library(tidyverse)
library(reshape2)
library(optparse)
library(cowplot)


option_list = list(
  make_option(c("-P", "--pheno"), action="store", default=NA, type='character',
              help="input pheno file"),
  make_option(c("-G", "--geno"), action="store", default=NA, type='character',
              help="input genotype"),
  make_option(c("-g", "--gene"), action="store", default=NA, type='character',
              help="gene"),
  make_option(c("-p", "--peakID"), action="store", default=NA, type='character',
              help="peakID"),
  make_option(c("-o", "--output"), action="store", default=NA, type='character',
              help="output file for plot")
)

opt_parser <- OptionParser(option_list=option_list)
opt <- parse_args(opt_parser)


opt_parser <- OptionParser(option_list=option_list)
opt <- parse_args(opt_parser)


phenohead=read.table("/project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/Phenotypeheader.txt", header = T,stringsAsFactors = F)
pheno=read.table(opt$pheno, col.names =colnames(phenohead),stringsAsFactors = F)


meltpheno=melt(pheno, id.vars = "chrom", value.name = "Ratio", variable.name = "Individual") %>% separate(Ratio, into=c("num", "denom"), sep="/")  %>%   separate(chrom, into=c("chrom", "start", "end", "peakID"),sep=":") %>% mutate(PeakLoc=paste(start, end, sep=":"))

meltpheno$Individual= as.character(meltpheno$Individual)
meltpheno$num= as.numeric(meltpheno$num)
meltpheno$denom=as.numeric(meltpheno$denom)


genoHead=read.table("/project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/genotypeHeader.txt", header = T,stringsAsFactors = F)
geno=read.table(opt$geno, col.names =colnames(genoHead),stringsAsFactors = F ) %>% select(ID,contains("NA")) 


lettersGeno=read.table(opt$geno, col.names =colnames(genoHead),stringsAsFactors = F,colClasses = c("character")) %>% select(REF, ALT)

refAllele=lettersGeno$REF
altAllele=lettersGeno$ALT


genoMelt=melt(geno, id.vars = "ID", value.name = "FullGeno", variable.name = "Individual" ) %>% separate(FullGeno, into=c("geno","dose","extra1"), sep=":") %>% select(Individual, dose) %>% mutate(genotype=ifelse(round(as.integer(dose))==0, paste(refAllele, refAllele, sep=""), ifelse(round(as.integer(dose))==1, paste(refAllele,altAllele, sep=""), paste(altAllele,altAllele,sep=""))))
genoMelt$Individual= as.character(genoMelt$Individual)


pheno_qtlpeak=meltpheno %>% inner_join(genoMelt, by="Individual") %>%  mutate(PAU=num/denom) 

qtlplot=ggplot(pheno_qtlpeak, aes(x=genotype, y=PAU, fill=genotype)) + geom_boxplot(width=.5)+ geom_jitter(alpha=1) + facet_grid(~PeakLoc) +scale_fill_brewer(palette = "YlOrRd")

ggsave(plot=qtlplot, filename=opt$output, height=10, width=10)

qtlHeatmapandFacetBoxplots.sh

#!/bin/bash

#SBATCH --job-name=qtlHeatmapandFacetBoxplots
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=qtlHeatmapandFacetBoxplots.out
#SBATCH --error=qtlHeatmapandFacetBoxplots.err
#SBATCH --partition=broadwl
#SBATCH --mem=18G
#SBATCH --mail-type=END


module load Anaconda3
source activate three-prime-env

Fraction=$1
gene=$2
chrom=$3
snp=$4
peakID=$5


less /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakTranscript_noMP_GeneLocAnno_5percUs/filtered_APApeaks_merged_allchrom_refseqGenes.GeneLocAnno_NoMP_sm_quant.${Fraction}.fixed.pheno_5perc.fc.gz | grep ${gene}_ > /project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/${gene}_${Fraction}PeaksPheno.txt


less /project2/gilad/briana/YRI_geno_hg19/chr${chrom}.dose.filt.vcf.gz | grep ${snp} > /project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/${gene}_${Fraction}PeaksGenotype.txt


Rscript makeQTLheatmap.R -P /project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/${gene}_${Fraction}PeaksPheno.txt -G  /project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/${gene}_${Fraction}PeaksGenotype.txt -g ${gene} -o /project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/${gene}_${Fraction}${SNP}${peakID}_heatmap.png


Rscript apaqtlfacetboxplots.R -P /project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/${gene}_${Fraction}PeaksPheno.txt -G  /project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/${gene}_${Fraction}PeaksGenotype.txt --gene ${gene} -p ${peakID}  -o /project2/gilad/briana/threeprimeseq/data/ExampleQTLPlots2/${gene}_${Fraction}${SNP}${peakID}_boxplot.png

sbatch qtlHeatmapandFacetBoxplots.sh "Nuclear" "DPP9" "19" "19:4680128" "peak77244"

sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14.1

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/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] cowplot_0.9.4   reshape2_1.4.3  forcats_0.4.0   stringr_1.4.0  
 [5] dplyr_0.8.0.1   purrr_0.3.1     readr_1.3.1     tidyr_0.8.3    
 [9] tibble_2.0.1    ggplot2_3.1.0   tidyverse_1.2.1

loaded via a namespace (and not attached):
 [1] tidyselect_0.2.5   xfun_0.5           haven_2.1.0       
 [4] lattice_0.20-38    colorspace_1.4-0   generics_0.0.2    
 [7] htmltools_0.3.6    yaml_2.2.0         rlang_0.3.1       
[10] pillar_1.3.1       glue_1.3.0         withr_2.1.2       
[13] RColorBrewer_1.1-2 modelr_0.1.4       readxl_1.3.0      
[16] plyr_1.8.4         munsell_0.5.0      gtable_0.2.0      
[19] workflowr_1.2.0    cellranger_1.1.0   rvest_0.3.2       
[22] evaluate_0.13      labeling_0.3       knitr_1.21        
[25] broom_0.5.1        Rcpp_1.0.0         scales_1.0.0      
[28] backports_1.1.3    jsonlite_1.6       fs_1.2.6          
[31] hms_0.4.2          digest_0.6.18      stringi_1.3.1     
[34] grid_3.5.1         rprojroot_1.3-2    cli_1.0.1         
[37] tools_3.5.1        magrittr_1.5       lazyeval_0.2.1    
[40] crayon_1.3.4       whisker_0.3-2      pkgconfig_2.0.2   
[43] xml2_1.2.0         lubridate_1.7.4    assertthat_0.2.0  
[46] rmarkdown_1.11     httr_1.4.0         rstudioapi_0.9.0  
[49] R6_2.4.0           nlme_3.1-137       git2r_0.24.0      
[52] compiler_3.5.1

Example facet boxplots

Briana Mittleman

4/15/2019