Perhaps this is related to the bigger problem (posted previously) that I have been encountering and would like to let you know why I came to this step 
While working on the single cell RNAseq analysis (did initially with R 3.6.1 around 2020/03~2020/08), I was able to get to the point of UMAPs and list of feature genes using Seurat. However, I found out several packages, especially for the advanced downstream analyses such as gene enrichment and differential analysis call for R 4; Therefore, I decided to upgrade to R 4 while locked the environment with renv. (even though I do not know quite well enough how to use it). After done this (changed my working environment), the UMAP is different from what I have done. Intuitive thinking, therefore, was to downgrade my R back to R 3.6.1. Unfortunately, I found out that this version of R is out.
In other words, is this possible to replicate what I have done before ? Please see the sessionInfo () from previous analysis
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.6
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.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] cowplot_1.0.0 scales_1.1.0 RCurl_1.98-1.1 Matrix_1.2-18 forcats_0.5.0
[6] stringr_1.4.0 dplyr_0.8.5 purrr_0.3.3 readr_1.3.1 tidyr_1.0.2
[11] tibble_2.1.3 ggplot2_3.2.1 tidyverse_1.3.0
loaded via a namespace (and not attached):
[1] nlme_3.1-141 fs_1.3.2 bitops_1.0-6 lubridate_1.7.4
[5] RcppAnnoy_0.0.16 RColorBrewer_1.1-2 httr_1.4.1 numDeriv_2016.8-1.1
[9] tools_3.6.1 backports_1.1.5 R6_2.4.0 irlba_2.3.3
[13] KernSmooth_2.23-15 DBI_1.1.0 lazyeval_0.2.2 colorspace_1.4-1
[17] sn_1.5-5 withr_2.1.2 npsurv_0.4-0 tidyselect_1.0.0
[21] mnormt_1.5-6 compiler_3.6.1 cli_2.0.1 rvest_0.3.5
[25] xml2_1.2.5 TFisher_0.2.0 sandwich_2.5-1 caTools_1.18.0
[29] lmtest_0.9-37 mvtnorm_1.0-11 ggridges_0.5.2 rappdirs_0.3.1
[33] digest_0.6.23 pkgconfig_2.0.3 bibtex_0.4.2.2 dbplyr_1.4.2
[37] readxl_1.3.1 rlang_0.4.5 rstudioapi_0.11 generics_0.0.2
[41] zoo_1.8-7 jsonlite_1.6.1 ica_1.0-2 gtools_3.8.1
[45] magrittr_1.5 fansi_0.4.1 Rcpp_1.0.2 munsell_0.5.0
[49] ape_5.3 reticulate_1.14 lifecycle_0.2.0 stringi_1.4.5
[53] multcomp_1.4-12 gbRd_0.4-11 MASS_7.3-51.4 gplots_3.0.3
[57] Rtsne_0.15 plyr_1.8.5 grid_3.6.1 parallel_3.6.1
[61] gdata_2.18.0 listenv_0.8.0 ggrepel_0.8.2 crayon_1.3.4
[65] lattice_0.20-38 haven_2.2.0 splines_3.6.1 hms_0.5.3
[69] pillar_1.4.3 igraph_1.2.4.1 future.apply_1.4.0 codetools_0.2-16
[73] stats4_3.6.1 leiden_0.3.3 reprex_0.3.0 glue_1.3.1
[77] lsei_1.2-0 modelr_0.1.6 BiocManager_1.30.10 vctrs_0.2.4
[81] Rdpack_0.11-1 cellranger_1.1.0 gtable_0.3.0 RANN_2.6.1
[85] future_1.16.0 assertthat_0.2.1 broom_0.5.5 survival_2.44-1.1
[89] cluster_2.1.0 globals_0.12.5 fitdistrplus_1.0-14 TH.data_1.0-10
[93] ROCR_1.0-7