Last updated: 2019-03-04
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These plots show the level of expression diversity among all Frontal cortex cells. Cells are colored based on cell class.
Version | Author | Date |
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a1bf7ee | Yasin Kaymaz | 2019-03-04 |
Excitatory (Ex) and inhibitory (In) neuronal subtypes in the cortex; distinct cerebellar granule (Gran) cells and Purkinje (Purk) neurons; and non-neuronal cells, including endothelial (End) cells, smooth muscle cells or pericytes, astrocytes (Ast), oligodendrocytes (Oli) and their precursor cells (OPCs), and microglia (Mic).
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sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin17.5.0 (64-bit)
Running under: macOS 10.14.3
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libLAPACK.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] bindrcpp_0.2.2 forcats_0.3.0 stringr_1.4.0 purrr_0.2.5
[5] readr_1.1.1 tidyr_0.8.1 tibble_2.0.1 tidyverse_1.2.1
[9] dplyr_0.7.6 Seurat_2.3.3 Matrix_1.2-14 cowplot_0.9.3
[13] here_0.1 DT_0.4 plotly_4.8.0 ggplot2_3.1.0
loaded via a namespace (and not attached):
[1] diffusionMap_1.1-0 Rtsne_0.15 colorspace_1.4-0
[4] class_7.3-14 modeltools_0.2-22 ggridges_0.5.0
[7] mclust_5.4.1 rprojroot_1.3-2 htmlTable_1.12
[10] base64enc_0.1-3 rstudioapi_0.8 proxy_0.4-22
[13] flexmix_2.3-14 bit64_0.9-7 lubridate_1.7.4
[16] mvtnorm_1.0-8 xml2_1.2.0 codetools_0.2-15
[19] splines_3.5.0 R.methodsS3_1.7.1 robustbase_0.93-1
[22] knitr_1.20 Formula_1.2-3 jsonlite_1.6
[25] workflowr_1.1.1 broom_0.5.0 ica_1.0-2
[28] cluster_2.0.7-1 kernlab_0.9-26 png_0.1-7
[31] R.oo_1.22.0 compiler_3.5.0 httr_1.3.1
[34] backports_1.1.2 assertthat_0.2.0 lazyeval_0.2.1
[37] cli_1.0.1 lars_1.2 acepack_1.4.1
[40] htmltools_0.3.6 tools_3.5.0 igraph_1.2.1
[43] gtable_0.2.0 glue_1.3.0 reshape2_1.4.3
[46] RANN_2.6 Rcpp_1.0.0 cellranger_1.1.0
[49] trimcluster_0.1-2 gdata_2.18.0 ape_5.1
[52] nlme_3.1-137 iterators_1.0.10 fpc_2.1-11
[55] lmtest_0.9-36 rvest_0.3.2 irlba_2.3.2
[58] gtools_3.8.1 DEoptimR_1.0-8 zoo_1.8-3
[61] MASS_7.3-50 scales_1.0.0 hms_0.4.2
[64] doSNOW_1.0.16 parallel_3.5.0 RColorBrewer_1.1-2
[67] yaml_2.2.0 reticulate_1.9 pbapply_1.4-0
[70] gridExtra_2.3 segmented_0.5-3.0 rpart_4.1-13
[73] latticeExtra_0.6-28 stringi_1.2.4 foreach_1.4.4
[76] checkmate_1.8.5 caTools_1.17.1 SDMTools_1.1-221
[79] rlang_0.3.1 pkgconfig_2.0.2 dtw_1.20-1
[82] prabclus_2.2-6 bitops_1.0-6 evaluate_0.10.1
[85] lattice_0.20-35 ROCR_1.0-7 bindr_0.1.1
[88] labeling_0.3 htmlwidgets_1.2 bit_1.1-14
[91] tidyselect_0.2.4 plyr_1.8.4 magrittr_1.5
[94] R6_2.3.0 snow_0.4-3 gplots_3.0.1
[97] Hmisc_4.1-1 haven_1.1.2 pillar_1.3.1
[100] whisker_0.3-2 foreign_0.8-70 withr_2.1.2
[103] mixtools_1.1.0 fitdistrplus_1.0-9 survival_2.42-6
[106] scatterplot3d_0.3-41 nnet_7.3-12 tsne_0.1-3
[109] modelr_0.1.2 crayon_1.3.4 hdf5r_1.0.1
[112] KernSmooth_2.23-15 rmarkdown_1.10 readxl_1.1.0
[115] grid_3.5.0 data.table_1.11.4 git2r_0.23.0
[118] metap_0.9 digest_0.6.18 diptest_0.75-7
[121] R.utils_2.6.0 stats4_3.5.0 munsell_0.5.0
[124] viridisLite_0.3.0
This reproducible R Markdown analysis was created with workflowr 1.1.1