Figure S7

Setting important directories

Also loading important libraries and custom functions for analysis.

seq_dir <- "/Volumes/PAULHOOK/sc-da-parkinsons/data"
file_dir <- "/Volumes/PAULHOOK/sc-da-parkinsons/output"
Rdata_dir <- "/Volumes/PAULHOOK/sc-da-parkinsons/data"
Script_dir <- "/Volumes/PAULHOOK/sc-da-parkinsons/code"
source(file.path(Script_dir,'init.R'))
source(file.path(Script_dir,"tools_R.r"))

#loading any special libraries
library(readr)
library(cowplot)
library(forcats)
library(reshape2)

Loading in data need

The final PD GWAS gene scoring data frame was loaded in.

final.gwas.table <- read.delim(file = file.path(file_dir, "PD.GWAS.Score.Final.txt"))

Figure S7A

Since ‘gene_biotype’ was included in the information extracted for each gene, we plotted the number of genes with each particular biotype in our data.

# Make bar plot for genes by gene_biotype
gwas.gene.biotype.df <- final.gwas.table %>%
  filter(is.na(MouseSymbol)) %>%
  group_by(gene_biotype)

## Warning: package 'bindrcpp' was built under R version 3.3.2

biotype.plot <- ggplot(gwas.gene.biotype.df, aes(x= fct_rev(fct_infreq(gene_biotype)))) + 
  geom_bar(fill = "gray48") + 
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_blank(),   axis.line = element_line(colour = "black"), plot.title = element_text(hjust = 0.5)) +
  xlab("Gene Biotype") + ylab("Number of genes without a defined mouse homolog") +
  ggtitle("Biotype frequency of genes in PD GWAS loci\nwithout mouse homologs identified through MGI") +
  coord_flip() + scale_y_continuous(limits = c(0,210), expand = c(0,0)) +
  stat_count(aes(label=paste(..count..)), vjust=0.5, hjust = -0.5,geom="text", color = "brown4", size = 5)

biotype.plot

Figure S7B

We plotted the number of protein coding genes without a mouse homolog in each locus.

# Make bar plot for protein coding genes without homologs by locus
gwas.gene.locus.df <- final.gwas.table %>%
  filter(is.na(MouseSymbol)) %>%
  group_by(locus) %>%
  filter(gene_biotype == "protein_coding")

locus.plot <- ggplot(gwas.gene.locus.df, aes(x= fct_rev(fct_infreq(snp)))) + 
  geom_bar(fill = "grey48") +
  xlab("Human PD Locus") + ylab("Number of protein coding genes without identified mouse homologs") +
  ggtitle("Frequency of protein coding genes in each PD GWAS locus\nwithout mouse homologs identified through NCBI Homologene ") + 
  scale_x_discrete(drop = F) + coord_flip() + scale_y_continuous(limits = c(0,15),expand = c(0,0)) +
  stat_count(aes(label=paste(..count..)), vjust=0.5, hjust = -0.5,geom="text", color = "brown4", size = 3) + 
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_blank(),   axis.line = element_line(colour = "black"), plot.title = element_text(hjust = 0.5))

locus.plot

Session Info

sessionInfo()

## R version 3.3.0 (2016-05-03)
## Platform: x86_64-apple-darwin13.4.0 (64-bit)
## Running under: OS X 10.11.6 (El Capitan)
## 
## 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] grid      splines   stats4    parallel  stats     graphics  grDevices
##  [8] utils     datasets  methods   base     
## 
## other attached packages:
##  [1] bindrcpp_0.2        forcats_0.2.0       cowplot_0.9.2      
##  [4] readr_1.1.1         ggbiplot_0.55       scales_0.5.0       
##  [7] SC3_1.1.4           ROCR_1.0-7          jackstraw_1.1.1    
## [10] lfa_1.2.2           tsne_0.1-3          gridExtra_2.3      
## [13] slackr_1.4.2        vegan_2.4-4         permute_0.9-4      
## [16] MASS_7.3-47         gplots_3.0.1        RColorBrewer_1.1-2 
## [19] Hmisc_4.0-3         Formula_1.2-2       survival_2.41-3    
## [22] lattice_0.20-35     Heatplus_2.18.0     Rtsne_0.13         
## [25] pheatmap_1.0.8      tidyr_0.7.1         dplyr_0.7.4        
## [28] plyr_1.8.4          heatmap.plus_1.3    stringr_1.2.0      
## [31] marray_1.50.0       limma_3.28.21       reshape2_1.4.3     
## [34] monocle_2.2.0       DDRTree_0.1.5       irlba_2.2.1        
## [37] VGAM_1.0-2          ggplot2_2.2.1       Biobase_2.32.0     
## [40] BiocGenerics_0.18.0 Matrix_1.2-11      
## 
## loaded via a namespace (and not attached):
##  [1] RSelenium_1.7.1        colorspace_1.3-2       class_7.3-14          
##  [4] rprojroot_1.2          htmlTable_1.9          corpcor_1.6.9         
##  [7] base64enc_0.1-3        mvtnorm_1.0-6          codetools_0.2-15      
## [10] doParallel_1.0.11      robustbase_0.92-7      knitr_1.17            
## [13] jsonlite_1.5           cluster_2.0.6          semver_0.2.0          
## [16] shiny_1.0.5            rrcov_1.4-3            httr_1.3.1            
## [19] backports_1.1.1        assertthat_0.2.0       lazyeval_0.2.1        
## [22] acepack_1.4.1          htmltools_0.3.6        tools_3.3.0           
## [25] igraph_1.1.2           gtable_0.2.0           glue_1.1.1            
## [28] binman_0.1.0           doRNG_1.6.6            Rcpp_0.12.14          
## [31] slam_0.1-37            gdata_2.18.0           nlme_3.1-131          
## [34] iterators_1.0.8        mime_0.5               rngtools_1.2.4        
## [37] gtools_3.5.0           WriteXLS_4.0.0         XML_3.98-1.9          
## [40] DEoptimR_1.0-8         hms_0.3                yaml_2.1.15           
## [43] pkgmaker_0.22          rpart_4.1-11           fastICA_1.2-1         
## [46] latticeExtra_0.6-28    stringi_1.1.5          pcaPP_1.9-72          
## [49] foreach_1.4.3          e1071_1.6-8            checkmate_1.8.4       
## [52] caTools_1.17.1         rlang_0.1.6            pkgconfig_2.0.1       
## [55] matrixStats_0.52.2     bitops_1.0-6           qlcMatrix_0.9.5       
## [58] evaluate_0.10.1        purrr_0.2.4            bindr_0.1             
## [61] labeling_0.3           htmlwidgets_0.9        magrittr_1.5          
## [64] R6_2.2.2               combinat_0.0-8         wdman_0.2.2           
## [67] foreign_0.8-69         mgcv_1.8-22            nnet_7.3-12           
## [70] tibble_1.3.4           KernSmooth_2.23-15     rmarkdown_1.8         
## [73] data.table_1.10.4      HSMMSingleCell_0.106.2 digest_0.6.12         
## [76] xtable_1.8-2           httpuv_1.3.5           openssl_0.9.7         
## [79] munsell_0.4.3          registry_0.3