Warning message: “package ‘Seurat’ was built under R version 4.3.2”

[ASNbioinf]

In my conda environment, I install Seurat (v5.0.1) and R(v4.3.1). When I load my package I have this warning:

set.seed(123)
.libPaths("/my/env/path/Seurat")
library(Seurat)

Warning message:
“package ‘Seurat’ was built under R version 4.3.2”

I have seen that several people have this warning. Nevertheless, they continue to develop their pipeline regardless of the warming. My question is actually could this situation affect my analysis with Seurat(v5.0.1)?

sessionInfo()
R version 4.3.1 (2023-06-16)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Debian GNU/Linux 10 (buster)

Matrix products: default
BLAS/LAPACK: /my/env/path/Seurat/lib/libopenblasp-r0.3.24.so; LAPACK version 3.11.0

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

time zone: Europe/Rome
tzcode source: system (glibc)

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

other attached packages:
[1] scRepertoire_1.10.0 ggplot2_3.5.1 dplyr_1.1.4
[4] Seurat_5.0.1 SeuratObject_5.0.0 sp_2.1-4

loaded via a namespace (and not attached):
[1] cubature_2.1.1 RcppAnnoy_0.0.21
[3] splines_4.3.1 later_1.3.1
[5] pbdZMQ_0.3-10 bitops_1.0-9
[7] tibble_3.2.1 polyclip_1.10-7
[9] fastDummies_1.7.3 lifecycle_1.0.3
[11] doParallel_1.0.17 globals_0.16.3
[13] lattice_0.21-9 MASS_7.3-60
[15] magrittr_2.0.3 plotly_4.10.2
[17] httpuv_1.6.11 sctransform_0.4.1
[19] spam_2.11-0 spatstat.sparse_3.0-2
[21] reticulate_1.34.0 cowplot_1.1.3
[23] pbapply_1.7-2 RColorBrewer_1.1-3
[25] abind_1.4-8 zlibbioc_1.48.2
[27] Rtsne_0.16 GenomicRanges_1.54.1
[29] purrr_1.0.2 ggraph_2.1.0
[31] BiocGenerics_0.48.1 RCurl_1.98-1.12
[33] tweenr_2.0.3 evmix_2.12
[35] GenomeInfoDbData_1.2.11 IRanges_2.36.0
[37] S4Vectors_0.40.2 ggrepel_0.9.6
[39] irlba_2.3.5.1 listenv_0.9.1
[41] spatstat.utils_3.0-3 vegan_2.6-4
[43] goftest_1.2-3 RSpectra_0.16-1
[45] spatstat.random_3.1-6 fitdistrplus_1.1-11
[47] parallelly_1.38.0 permute_0.9-7
[49] leiden_0.4.3 codetools_0.2-19
[51] DelayedArray_0.28.0 ggforce_0.4.2
[53] tidyselect_1.2.1 farver_2.1.2
[55] viridis_0.6.4 matrixStats_1.4.1
[57] stats4_4.3.1 base64enc_0.1-3
[59] spatstat.explore_3.2-3 jsonlite_1.8.7
[61] ellipsis_0.3.2 tidygraph_1.3.1
[63] progressr_0.14.0 iterators_1.0.14
[65] ggridges_0.5.4 ggalluvial_0.12.5
[67] survival_3.5-7 foreach_1.5.2
[69] tools_4.3.1 stringdist_0.9.10
[71] ica_1.0-3 Rcpp_1.0.13
[73] glue_1.6.2 gridExtra_2.3
[75] SparseArray_1.2.4 mgcv_1.9-0
[77] MatrixGenerics_1.12.2 GenomeInfoDb_1.38.8
[79] IRdisplay_1.1 withr_3.0.1
[81] fastmap_1.1.1 fansi_1.0.5
[83] SparseM_1.84-2 digest_0.6.33
[85] R6_2.5.1 mime_0.12
[87] colorspace_2.1-1 scattermore_1.2
[89] tensor_1.5 spatstat.data_3.0-1
[91] utf8_1.2.3 tidyr_1.3.1
[93] generics_0.1.3 data.table_1.14.8
[95] graphlayouts_1.2.0 httr_1.4.7
[97] htmlwidgets_1.6.2 S4Arrays_1.2.1
[99] uwot_0.1.16 pkgconfig_2.0.3
[101] gtable_0.3.5 lmtest_0.9-40
[103] SingleCellExperiment_1.24.0 XVector_0.42.0
[105] powerTCR_1.20.0 htmltools_0.5.6.1
[107] dotCall64_1.2 scales_1.3.0
[109] Biobase_2.62.0 png_0.1-8
[111] ggdendro_0.2.0 reshape2_1.4.4
[113] uuid_1.1-1 nlme_3.1-163
[115] repr_1.1.6 zoo_1.8-12
[117] stringr_1.5.1 KernSmooth_2.23-22
[119] parallel_4.3.1 miniUI_0.1.1.1
[121] pillar_1.9.0 grid_4.3.1
[123] vctrs_0.6.4 RANN_2.6.1
[125] VGAM_1.1-12 promises_1.2.1
[127] xtable_1.8-4 cluster_2.1.4
[129] evaluate_0.22 truncdist_1.0-2
[131] cli_3.6.1 compiler_4.3.1
[133] rlang_1.1.1 crayon_1.5.2
[135] future.apply_1.11.2 plyr_1.8.9
[137] stringi_1.8.4 viridisLite_0.4.2
[139] deldir_1.0-9 assertthat_0.2.1
[141] munsell_0.5.1 gsl_2.1-8
[143] lazyeval_0.2.2 spatstat.geom_3.2-5
[145] Matrix_1.6-1.1 IRkernel_1.3.2
[147] RcppHNSW_0.5.0 patchwork_1.1.3
[149] future_1.34.0 shiny_1.7.5.1
[151] SummarizedExperiment_1.32.0 evd_2.3-6.1
[153] ROCR_1.0-11 igraph_2.0.3