Installation

Requirements

EpiTrace requires R 4.0 or later. The current recommended environment is R 4.1.3.

You will need a working compiler and working internet connection in an environment where you can successfully install Seurat and Signac (most dependencies coming from Seurat). We have tested installation of EpiTrace in freshly-installed R-4.3.2 on MacOS with XCODE supplied clang, and R-4.2.0 on Linux, using the following steps.

Installation on Windows has not been tested.

Simple install

We recommend to install EpiTrace using pak. It seems that pak handles dependencies hosted on different sources well.

Install EpiTrace from Github using:

if(!require(pak)){
    install.packages("pak")
}
library(pak)
pak::pkg_install('caleblareau/easyLift')
pak::pkg_install('MagpiePKU/EpiTrace')

If you encountered any issue in installation, please let us know by flagging up an issue here in Github.

Dependencies

  • dplyr

  • tidyr

  • RColorBrewer

  • ggplot2

  • Seurat (>=4.0)

  • SeuratObject

  • Signac (>= 1.5.0)

  • GenomicRanges

  • plyranges (>= 1.0)

  • WGCNA (>= 1.7)

  • stringr

  • easyLift

  • parallel

  • nnls

  • ggtree

  • ape

  • reticulate

  • ggpubr

  • Matrix

  • matrixStats

  • sparseMatrixStats

  • plyranges

Example installation log

Fresh installation on a newly installed R:

> pak::pkg_install('MagpiePKU/EpiTrace')

✔ Updated metadata database: 2.86 MB in 8 files.
✔ Updating metadata database ... done

→ Will install 223 packages.
→ Will update 1 package.
→ Will download 203 CRAN packages (163.12 MB).
→ Will download 21 packages with unknown size.
+ AnnotationDbi              1.64.1     👷🏾 ⬇
+ BH                         1.84.0-0   👷🏽‍♀️ ⬇ (14.02 MB)
+ Biobase                    2.62.0     👷🏼‍♀️🔧 ⬇
+ BiocGenerics               0.48.1     👷🏻 ⬇

....

ℹ Packaging EpiTrace 0.0.1.3
✔ Packaged EpiTrace 0.0.1.3 (5.9s)
ℹ Building EpiTrace 0.0.1.3
✔ Built EpiTrace 0.0.1.3 (41.6s)
✔ Installed EpiTrace 0.0.1.3 (github::MagpiePKU/EpiTrace@38d36a6) (251ms)
✔ 1 pkg + 227 deps: kept 220, added 1, dld 1 (NA B) [1m 20.9s]

Example session info

Developer environment:

> sessionInfo()
  R version 4.2.0 (2022-04-22)
  Platform: aarch64-apple-darwin20 (64-bit)
  Running under: macOS 14.2

  Matrix products: default
  BLAS:   /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
  LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib

  locale:
  [1] C/UTF-8/C/C/C/C

  attached base packages:
  [1] parallel  stats4    stats     graphics  grDevices utils     datasets
  [8] methods   base

  other attached packages:
   [1] ggpubr_0.4.0          reticulate_1.25       ape_5.7-1
   [4] ggtree_3.4.0          nnls_1.4              HiClimR_2.2.1
   [7] ccaPP_0.3.3           robustbase_0.95-0     pcaPP_2.0-1
  [10] sva_3.44.0            BiocParallel_1.30.2   genefilter_1.78.0
  [13] mgcv_1.8-40           nlme_3.1-157          easyLift_0.2.1
  [16] stringr_1.4.0         WGCNA_1.71            fastcluster_1.2.3
  [19] dynamicTreeCut_1.63-1 plyranges_1.16.0      GenomicRanges_1.48.0
  [22] GenomeInfoDb_1.34.9   IRanges_2.30.0        S4Vectors_0.34.0
  [25] BiocGenerics_0.42.0   ggplot2_3.3.6         RColorBrewer_1.1-3
  [28] tidyr_1.2.0           dplyr_1.1.4           Signac_1.6.0
  [31] sp_1.4-7              SeuratObject_4.1.0    Seurat_4.1.1
  [34] EpiTrace_0.0.0.9000

Tested installation environment:

> sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: aarch64-apple-darwin23.2.0 (64-bit)
Running under: macOS Sonoma 14.2

Matrix products: default
BLAS:   /Users/wing/Desktop/Eulerian/文件/内部研发项目/CLOCK_CANCER/Clock_Evolution/test_install/R-4.3.2/lib/libRblas.dylib
LAPACK: /Users/wing/Desktop/Eulerian/文件/内部研发项目/CLOCK_CANCER/Clock_Evolution/test_install/R-4.3.2/lib/libRlapack.dylib;  LAPACK version 3.11.0

locale:
[1] C/UTF-8/C/C/C/C

time zone: Asia/Shanghai
tzcode source: internal

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

other attached packages:
[1] EpiTrace_0.0.1.3 pak_0.7.1

loaded via a namespace (and not attached):
  [1] RcppAnnoy_0.0.22            splines_4.3.2
  [3] later_1.3.2                 BiocIO_1.12.0
  [5] ggplotify_0.1.2             bitops_1.0-7
  [7] easyLift_0.2.1              tibble_3.2.1
  [9] polyclip_1.10-6             preprocessCore_1.64.0
 [11] rpart_4.1.21                XML_3.99-0.16.1
 [13] fastDummies_1.7.3           lifecycle_1.0.4
 [15] fastcluster_1.2.6           doParallel_1.0.17
 [17] globals_0.16.2              lattice_0.21-9
 [19] MASS_7.3-60                 backports_1.4.1
 [21] magrittr_2.0.3              rmarkdown_2.25
 [23] Hmisc_5.1-1                 plotly_4.10.4
 [25] yaml_2.3.8                  httpuv_1.6.14
 [27] Seurat_5.0.1                sctransform_0.4.1
 [29] spam_2.10-0                 sp_2.1-2
 [31] spatstat.sparse_3.0-3       reticulate_1.34.0
 [33] cowplot_1.1.3               pbapply_1.7-2
 [35] DBI_1.2.1                   RColorBrewer_1.1-3
 [37] abind_1.4-5                 zlibbioc_1.48.0
 [39] Rtsne_0.17                  GenomicRanges_1.54.1
 [41] purrr_1.0.2                 BiocGenerics_0.48.1
 [43] RCurl_1.98-1.14             yulab.utils_0.1.3
 [45] nnet_7.3-19                 GenomeInfoDbData_1.2.11
 [47] IRanges_2.36.0              S4Vectors_0.40.2
 [49] ggrepel_0.9.5               irlba_2.3.5.1
 [51] listenv_0.9.0               spatstat.utils_3.0-4
 [53] tidytree_0.4.6              goftest_1.2-3
 [55] RSpectra_0.16-1             spatstat.random_3.2-2
 [57] fitdistrplus_1.1-11         parallelly_1.36.0
 [59] leiden_0.4.3.1              codetools_0.2-19
 [61] DelayedArray_0.28.0         RcppRoll_0.3.0
 [63] tidyselect_1.2.0            aplot_0.2.2
 [65] base64enc_0.1-3             matrixStats_1.2.0
 [67] stats4_4.3.2                dynamicTreeCut_1.63-1
 [69] spatstat.explore_3.2-5      GenomicAlignments_1.38.2
 [71] jsonlite_1.8.8              Formula_1.2-5
 [73] ellipsis_0.3.2              progressr_0.14.0
 [75] ggridges_0.5.6              survival_3.5-7
 [77] iterators_1.0.14            foreach_1.5.2
 [79] tools_4.3.2                 treeio_1.26.0
 [81] ica_1.0-3                   Rcpp_1.0.12
 [83] glue_1.7.0                  gridExtra_2.3
 [85] SparseArray_1.2.3           xfun_0.41
 [87] MatrixGenerics_1.14.0       GenomeInfoDb_1.38.5
 [89] dplyr_1.1.4                 fastmap_1.1.1
 [91] fansi_1.0.6                 digest_0.6.34
 [93] gridGraphics_0.5-1          R6_2.5.1
 [95] mime_0.12                   colorspace_2.1-0
 [97] scattermore_1.2             GO.db_3.18.0
 [99] tensor_1.5                  RSQLite_2.3.5
[101] spatstat.data_3.0-4         utf8_1.2.4
[103] tidyr_1.3.1                 generics_0.1.3
[105] data.table_1.14.10          rtracklayer_1.62.0
[107] httr_1.4.7                  htmlwidgets_1.6.4
[109] S4Arrays_1.2.0              uwot_0.1.16
[111] pkgconfig_2.0.3             gtable_0.3.4
[113] blob_1.2.4                  impute_1.76.0
[115] lmtest_0.9-40               XVector_0.42.0
[117] htmltools_0.5.7             dotCall64_1.1-1
[119] plyranges_1.22.0            SeuratObject_5.0.1
[121] scales_1.3.0                Biobase_2.62.0
[123] png_0.1-8                   ggfun_0.1.4
[125] rstudioapi_0.15.0           knitr_1.45
[127] Signac_1.12.0               reshape2_1.4.4
[129] rjson_0.2.21                checkmate_2.3.1
[131] nlme_3.1-163                cachem_1.0.8
[133] zoo_1.8-12                  stringr_1.5.1
[135] KernSmooth_2.23-22          parallel_4.3.2
[137] miniUI_0.1.1.1              foreign_0.8-85
[139] AnnotationDbi_1.64.1        restfulr_0.0.15
[141] pillar_1.9.0                grid_4.3.2
[143] vctrs_0.6.5                 RANN_2.6.1
[145] promises_1.2.1              xtable_1.8-4
[147] cluster_2.1.4               htmlTable_2.4.2
[149] evaluate_0.23               cli_3.6.2
[151] compiler_4.3.2              Rsamtools_2.18.0
[153] rlang_1.1.3                 crayon_1.5.2
[155] future.apply_1.11.1         fs_1.6.3
[157] plyr_1.8.9                  stringi_1.8.3
[159] nnls_1.5                    viridisLite_0.4.2
[161] deldir_2.0-2                WGCNA_1.72-5
[163] BiocParallel_1.36.0         munsell_0.5.0
[165] Biostrings_2.70.1           lazyeval_0.2.2
[167] spatstat.geom_3.2-8         Matrix_1.6-5
[169] RcppHNSW_0.5.0              patchwork_1.2.0
[171] bit64_4.0.5                 future_1.33.1
[173] ggplot2_3.4.4               KEGGREST_1.42.0
[175] shiny_1.8.0                 SummarizedExperiment_1.32.0
[177] ROCR_1.0-11                 memoise_2.0.1
[179] igraph_1.6.0                ggtree_3.10.0
[181] fastmatch_1.1-4             bit_4.0.5
[183] ape_5.7-1

Again, if you run into issues in installation or using, do not hesitate to approach us or raise a GitHub issue.