Single cell resolution landscape of equine peripheral blood mononuclear cells reveals diverse cell types including T-bet+ B cells.
This repository contains the data analysis scripts and code for our paper:
Roosheel S. Patel*, Joy E. Tomlinson*, Thomas J. Divers, Gerlinde R. Van de Walle, Brad R. Rosenberg, (2020). Single cell resolution landscape of equine peripheral blood mononuclear cells reveals diverse cell types including T-bet+ B cells. BMC Biology https://doi.org/10.1186/s12915-020-00947-5
*indicates equal contribution
The analysis directory contains:
- 📁 paper: R Markdown document which includes code to reproduce the figures generated by our analysis.
- 📁 data: Supplementary data files and metadata used in this analysis
For surface annotation of differentially expressed genes, surface protein annotations were pulled from the Cell Surface Protein Atlas website.
Bausch-Fluck D, Hofmann A, Bock T, Frei AP, Cerciello F, et al. (2015) A Mass Spectrometric-Derived Cell Surface Protein Atlas. PLoS One https://doi.org/10.1371/journal.pone.0121314
Code : MIT License, Copyright (c) 2020 Roosheel Patel
The organization of this repository was adapted from the rrtools research compendium structure
Marwick, B. (2017). Computational reproducibility in archaeological research: Basic principles and a case study of their implementation.Journal of Archaeological Method and Theory, 24(2), 424-450.https://doi.org/10.1007/s10816-015-9272-9
Session information (computer environment and R/package versions) used to generate the analyses and figures in the manuscript:
R version 3.6.2 (2019-12-12) Platform: x86_64-pc-linux-gnu (64-bit) Running under: CentOS Linux 7 (Core) Matrix products: default BLAS/LAPACK: /hpc/packages/minerva-centos7/intel/parallel_studio_xe_2019/compilers_and_libraries_2019.0.117/linux/mkl/lib/intel64_lin/libmkl_gf_lp64.so Random number generation: RNG: Mersenne-Twister Normal: Inversion Sample: Rounding 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
other attached packages: [1] readr_1.4.0 modelr_0.1.8 tidyr_1.1.2 reshape2_1.4.4 here_1.0.0 circlize_0.4.11 ComplexHeatmap_2.2.0 [8] GEOquery_2.54.1 factoextra_1.0.7 cluster_2.1.0 openxlsx_4.2.3 legocolors_0.2.0 ggforce_0.3.2 ggtree_2.0.4
[15] viridis_0.5.1 viridisLite_0.3.0 BiocManager_1.30.10 jntools_0.1.0 mgsub_1.7.2 ape_5.4-1 patchwork_1.1.0
[22] dplyr_1.0.2 edgeR_3.28.1 limma_3.42.2 scales_1.1.1 lemon_0.4.5 ggpubr_0.4.0 readxl_1.3.1
[29] ggrepel_0.8.2 RColorBrewer_1.1-2 ggnetwork_0.5.8 sctransform_0.2.0 uwot_0.1.9 rlang_0.4.9 rrtools_0.1.0
[36] future_1.20.1 clustree_0.4.3 ggraph_2.0.4 ggplot2_3.3.2 gdata_2.18.0 cowplot_1.1.0 gtools_3.8.2
[43] tibble_3.0.4 AnnotationDbi_1.48.0 IRanges_2.20.2 S4Vectors_0.24.4 Biobase_2.46.0 BiocGenerics_0.32.0 Matrix_1.2-18
[50] renv_0.12.3 Seurat_3.1.0
loaded via a namespace (and not attached): [1] reticulate_1.18 tidyselect_1.1.0 RSQLite_2.2.1 htmlwidgets_1.5.2 Rtsne_0.15 devtools_2.3.2
[7] munsell_0.5.0 codetools_0.2-18 ica_1.0-2 miniUI_0.1.1.1 withr_2.3.0 colorspace_2.0-0
[13] knitr_1.30 rstudioapi_0.13 ROCR_1.0-11 ggsignif_0.6.0 tensor_1.5 listenv_0.8.0
[19] labeling_0.4.2 git2r_0.27.1 polyclip_1.10-0 bit64_4.0.5 farver_2.0.3 rprojroot_2.0.2
[25] treeio_1.10.0 parallelly_1.21.0 vctrs_0.3.5 generics_0.1.0 xfun_0.19 R6_2.5.0
[31] clue_0.3-58 graphlayouts_0.7.1 rsvd_1.0.3 locfit_1.5-9.4 spatstat.utils_1.17-0 assertthat_0.2.1
[37] promises_1.1.1 gtable_0.3.0 globals_0.14.0 processx_3.4.5 goftest_1.2-2 tidygraph_1.2.0
[43] clisymbols_1.2.0 GlobalOptions_0.1.2 splines_3.6.1 rstatix_0.6.0 lazyeval_0.2.2 broom_0.7.2
[49] yaml_2.2.1 abind_1.4-5 backports_1.2.1 httpuv_1.5.4 tools_3.6.1 usethis_1.6.3
[55] bookdown_0.21 ellipsis_0.3.1 sessioninfo_1.1.1 ggridges_0.5.2 Rcpp_1.0.5 plyr_1.8.6
[61] purrr_0.3.4 ps_1.5.0 prettyunits_1.1.1 rpart_4.1-15 deldir_0.2-3 GetoptLong_1.0.4
[67] pbapply_1.4-3 zoo_1.8-8 haven_2.3.1 fs_1.5.0 magrittr_2.0.1 data.table_1.13.4
[73] lmtest_0.9-38 RANN_2.6.1 fitdistrplus_1.1-3 matrixStats_0.57.0 pkgload_1.1.0 hms_0.5.3
[79] mime_0.9 evaluate_0.14 xtable_1.8-4 rio_0.5.16 shape_1.4.5 gridExtra_2.3
[85] testthat_3.0.0 compiler_3.6.1 KernSmooth_2.23-18 crayon_1.3.4 htmltools_0.5.0 mgcv_1.8-33
[91] later_1.1.0.1 DBI_1.1.0 tweenr_1.0.1 MASS_7.3-53 car_3.0-10 cli_2.2.0
[97] igraph_1.2.6 forcats_0.5.0 pkgconfig_2.0.3 rvcheck_0.1.8 foreign_0.8-71 plotly_4.9.2.1
[103] xml2_1.3.2 stringr_1.4.0 callr_3.5.1 digest_0.6.27 RcppAnnoy_0.0.17 spatstat.data_1.5-2
[109] rmarkdown_2.5 cellranger_1.1.0 leiden_0.3.6 tidytree_0.3.3 curl_4.3 shiny_1.5.0
[115] rjson_0.2.20 lifecycle_0.2.0 nlme_3.1-150 jsonlite_1.7.1 carData_3.0-4 desc_1.2.0
[121] fansi_0.4.1 pillar_1.4.7 lattice_0.20-41 fastmap_1.0.1 httr_1.4.2 pkgbuild_1.1.0
[127] survival_3.2-7 glue_1.4.2 remotes_2.2.0 zip_2.1.1 spatstat_1.64-1 png_0.1-7
[133] bit_4.0.4 stringi_1.5.3 blob_1.2.1 memoise_1.1.0 irlba_2.3.3 future.apply_1.6.0