Sequencing depth per C1 chip

Setup

library("dplyr")
library("DT")
library("ggplot2")
library("reshape2")
library("Biobase")
theme_set(cowplot::theme_cowplot())

fname <- Sys.glob("../data/eset/*.rds")
eset <- Reduce(combine, Map(readRDS, fname))
pData(eset)$experiment <- as.factor(pData(eset)$experiment)

Total sequencing depth

ggplot(pData(eset), aes(x = raw, color = experiment)) +
  geom_density() +
  labs(x = "Number of raw sequences per single cell", y = "Number of cells",
       title = "Distribution of total raw sequences per single cell") +
  scale_color_discrete(name = "C1 chip")

Mapped reads per cell

ggplot(pData(eset), aes(x = experiment, y = mapped, color = experiment)) +
  geom_violin() + 
  geom_boxplot(alpha = .01, width = .2, position = position_dodge(width = .9)) +
  labs(x = "C1 chip", y = "Number of reads",
       title = "Number of mapped sequences per single cell") +
  theme(legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1))

Sum of sequences across the 96 single cells per C1 chip.

total_per_experiment <- pData(eset) %>%
  group_by(experiment) %>%
  summarize(raw = sum(raw) / 10^6,
            mapped = sum(mapped) / 10^6,
            molecules = sum(molecules) / 10^6)
datatable(total_per_experiment,
          options = list(pageLength = nrow(total_per_experiment)),
          colnames = c("C1 chip", "Number of raw sequences",
                       "Number of mapped",
                       "Number of molecules"))

ggplot(melt(total_per_experiment, id.vars = "experiment",
            variable.name = "type", value.name = "count"),
       aes(x = experiment, y = count, color = type)) +
  geom_point() +
  labs(title = "Sequencing depth per C1 chip",
       x = "C1 chip", y = "Number of sequences") +
  theme(legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1))

Session information

sessionInfo()

R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.2 (Nitrogen)

Matrix products: default
BLAS: /project2/gilad/jdblischak/miniconda3/envs/fucci-seq/lib/R/lib/libRblas.so
LAPACK: /project2/gilad/jdblischak/miniconda3/envs/fucci-seq/lib/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] bindrcpp_0.2        Biobase_2.38.0      BiocGenerics_0.24.0
[4] reshape2_1.4.2      ggplot2_2.2.1       DT_0.2             
[7] dplyr_0.7.4        

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.13     knitr_1.16       bindr_0.1        magrittr_1.5    
 [5] cowplot_0.9.1    munsell_0.4.3    colorspace_1.3-2 R6_2.2.0        
 [9] rlang_0.1.2      plyr_1.8.4       stringr_1.2.0    tools_3.4.1     
[13] grid_3.4.1       gtable_0.2.0     git2r_0.19.0     htmltools_0.3.6 
[17] lazyeval_0.2.0   yaml_2.1.14      rprojroot_1.2    digest_0.6.12   
[21] assertthat_0.1   tibble_1.3.3     htmlwidgets_0.9  glue_1.1.1      
[25] evaluate_0.10.1  rmarkdown_1.6    labeling_0.3     stringi_1.1.2   
[29] compiler_3.4.1   scales_0.5.0     backports_1.0.5  jsonlite_1.4    
[33] pkgconfig_2.0.1