Last update: 2018-01-18
Code version: 5996c19850dc5fc65723f30bc33ab1c8d083a7e6
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"))
e15.dat.filter <- readRDS(file = file.path(Rdata_dir, "e15.dat.filter.rds"))
## [1] 725
Viewing screeplots and determining the number of “significant” PCs
e15.Fb.clusters.df <- readRDS(file = file.path(Rdata_dir, "e15.Fb.clusters.df.rds"))
e15.Mb.clusters.df <- readRDS(file = file.path(Rdata_dir, "e15.Mb.clusters.df.rds"))
e15.Mb.clusters.df$subset.cluster <- paste0("E15.MB.",e15.Mb.clusters.df$kmeans_tSNE_cluster)
e15.Fb.clusters.df$subset.cluster <- paste0("E15.FB.",e15.Fb.clusters.df$kmeans_tSNE_cluster)
Sub.clusters.df <- rbind(e15.Mb.clusters.df,e15.Fb.clusters.df)
names(Sub.clusters.df) <- c("sample_id.x","remove","subset.cluster")
final.data.frame <- merge(x = pData(e15.dat.filter), y = Sub.clusters.df, by = "sample_id.x")
pData(e15.dat.filter)$subset.cluster <- as.factor(final.data.frame$subset.cluster)
myTSNEPlotAlpha(e15.dat.filter,color="subset.cluster", shape="region") + scale_color_brewer(palette="Set1") + ggtitle("E15.5 All - MB Specific Genes")
## Scale for 'colour' is already present. Adding another scale for
## 'colour', which will replace the existing scale.
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] ggbiplot_0.55 scales_0.5.0 SC3_1.1.4
## [4] ROCR_1.0-7 jackstraw_1.1.1 lfa_1.2.2
## [7] tsne_0.1-3 gridExtra_2.3 slackr_1.4.2
## [10] vegan_2.4-4 permute_0.9-4 MASS_7.3-47
## [13] gplots_3.0.1 RColorBrewer_1.1-2 Hmisc_4.0-3
## [16] Formula_1.2-2 survival_2.41-3 lattice_0.20-35
## [19] Heatplus_2.18.0 Rtsne_0.13 pheatmap_1.0.8
## [22] tidyr_0.7.1 dplyr_0.7.4 plyr_1.8.4
## [25] heatmap.plus_1.3 stringr_1.2.0 marray_1.50.0
## [28] limma_3.28.21 reshape2_1.4.3 monocle_2.2.0
## [31] DDRTree_0.1.5 irlba_2.2.1 VGAM_1.0-2
## [34] ggplot2_2.2.1 Biobase_2.32.0 BiocGenerics_0.18.0
## [37] 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] bindrcpp_0.2 igraph_1.1.2 gtable_0.2.0
## [28] glue_1.1.1 binman_0.1.0 doRNG_1.6.6
## [31] Rcpp_0.12.14 slam_0.1-37 gdata_2.18.0
## [34] nlme_3.1-131 iterators_1.0.8 mime_0.5
## [37] rngtools_1.2.4 gtools_3.5.0 WriteXLS_4.0.0
## [40] XML_3.98-1.9 DEoptimR_1.0-8 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
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