sgA = read.table(file = "raw/CRISPR_WG_libraryA.txt", row.names = 1, header = TRUE, sep = "\t")
control = filter(sgA, str_detect(Gene, 'NonTargeting')) %>% select(-Gene) %>%
summarise_each(function(z) sum(z > 5)/length(z)) %>% unlist()
sgRNA = filter(sgA, str_detect(Gene, 'NonTargeting', negate = TRUE)) %>%
select(-Gene) %>%
summarise_each(function(z) sum(z > 5)/length(z)) %>% unlist()
ATable = data.frame(name = names(sgRNA), library = "A", sgRNA, control)
sgB = read.table(file = "raw/CRISPR_WG_libraryB.txt", row.names = 1, header = TRUE, sep = "\t")
control = filter(sgB, str_detect(Gene, 'NonTargeting')) %>% select(-Gene) %>%
summarise_each(function(z) sum(z > 5)/length(z)) %>% unlist()
sgRNA = filter(sgB, str_detect(Gene, 'NonTargeting', negate = TRUE)) %>%
select(-Gene) %>%
summarise_each(function(z) sum(z > 5)/length(z)) %>% unlist()
BTable = data.frame(name = names(sgRNA), library = "B", sgRNA, control)
abTable = bind_rows(ATable, BTable)
group = rep("vivo", nrow(abTable))
group[grep("plasmid", abTable$name)] = "plasmid"
group[grep("Pre", abTable$name)] = "Pre"
group[grep("vitro", abTable$name)] = "vitro"
condition = rep("", nrow(abTable))
condition[grep("plasmid", abTable$name)] = "plasmid"
condition[grep("MA", abTable$name)] = "MA"
condition[grep("HM", abTable$name)] = "HM"
abTable = data.frame(abTable, group, condition)
head(abTable)
name library sgRNA control group condition
A_plasmid A_plasmid A 0.9780584 0.976 plasmid plasmid
MA_A_Pre_1 MA_A_Pre_1 A 0.7477102 0.775 Pre MA
MA_A_Pre_2 MA_A_Pre_2 A 0.7291897 0.760 Pre MA
HM_A_Pre_1 HM_A_Pre_1 A 0.8899342 0.901 Pre HM
HM_A_Pre_2 HM_A_Pre_2 A 0.8741350 0.882 Pre HM
MA_A_vitro_1 MA_A_vitro_1 A 0.6501314 0.674 vitro MA
table(condition, group)
group
condition Pre plasmid vitro vivo
HM 3 0 4 40
MA 4 0 4 40
plasmid 0 2 0 0
p <- ggplot(abTable, aes(x = group, y = sgRNA, color = condition))
p <- p + theme_bw() + labs(x = "condition", y = "Fraction of sgRNA covered\n(> 5x)", title = "targeting sgRNA")
p <- p + theme(plot.title = element_text(hjust = 0.5)) + geom_boxplot()
print(p)
p <- ggplot(abTable, aes(x = group, y = control, color = condition))
p <- p + theme_bw() + labs(x = "condition", y = "Fraction of sgRNA covered\n(> 5x)", title = "control sgRNA")
p <- p + theme(plot.title = element_text(hjust = 0.5)) + geom_boxplot()
print(p)
Given the limited coverage especially for in vivo condition, we pooled biological replicates to gain higher coverage.
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-conda_cos6-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux Server 7.7 (Maipo)
Matrix products: default
BLAS: /sibcb2/bioinformatics/software/BcbioNG/anaconda/lib/R/lib/libRblas.so
LAPACK: /sibcb2/bioinformatics/software/BcbioNG/anaconda/lib/R/lib/libRlapack.so
locale:
[1] C
attached base packages:
[1] parallel grid stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] stringr_1.4.0 viper_1.16.0 scales_1.1.0
[4] pheatmap_1.0.12 dplyr_1.0.5 survcomp_1.32.0
[7] prodlim_2019.11.13 RColorBrewer_1.1-2 gridExtra_2.3
[10] survHD_0.99.1 survC1_1.0-2 Hmisc_4.3-0
[13] Formula_1.2-3 lattice_0.20-38 penalized_0.9-51
[16] survival_3.1-8 Biobase_2.42.0 BiocGenerics_0.28.0
[19] VennDiagram_1.6.20 futile.logger_1.4.3 ggrepel_0.8.1
[22] ggplot2_3.2.1 rmarkdown_2.0
loaded via a namespace (and not attached):
[1] mixtools_1.1.0 splines_3.5.1 rmeta_3.0
[4] highr_0.8 latticeExtra_0.6-28 bootstrap_2019.6
[7] yaml_2.2.0 survivalROC_1.0.3 pillar_1.5.1
[10] backports_1.1.5 glue_1.4.2 digest_0.6.23
[13] checkmate_1.9.4 colorspace_1.4-1 htmltools_0.5.1.1
[16] Matrix_1.2-18 pkgconfig_2.0.3 purrr_0.3.3
[19] lava_1.6.7 htmlTable_1.13.3 tibble_3.1.0
[22] generics_0.0.2 farver_2.0.1 ellipsis_0.3.0
[25] withr_2.1.2 nnet_7.3-12 lazyeval_0.2.2
[28] magrittr_1.5 crayon_1.3.4 evaluate_0.14
[31] fansi_0.4.0 segmented_1.1-0 MASS_7.3-51.5
[34] class_7.3-15 foreign_0.8-74 SuppDists_1.1-9.5
[37] tools_3.5.1 data.table_1.12.8 formatR_1.7
[40] lifecycle_1.0.0 munsell_0.5.0 cluster_2.1.0
[43] lambda.r_1.2.4 e1071_1.7-3 compiler_3.5.1
[46] rlang_0.4.10 rstudioapi_0.10 htmlwidgets_1.5.1
[49] base64enc_0.1-3 labeling_0.3 gtable_0.3.0
[52] DBI_1.1.0 R6_2.4.1 knitr_1.26
[55] utf8_1.1.4 futile.options_1.0.1 KernSmooth_2.23-16
[58] stringi_1.4.3 Rcpp_1.0.3 vctrs_0.3.7
[61] rpart_4.1-15 acepack_1.4.1 tidyselect_1.1.0
[64] xfun_0.18