Hi! I am observing different statistics for DE analysis done in two separate runs executed on same count files. Apart from base mean, all other columns have different statistical numbers for every row.

Perplexing thing is that normalized counts are same for both the runs but pValues and log fold change values are still different. The only thing done differently from the earlier run is that I had to reinstall DESeq2. I do not remember the previous version that was installed. Can this be related to differences in the package versions?

Code should be placed in three backticks as shown below

R version 4.3.2 (2023-10-31)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.2

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

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

time zone: America/Los_Angeles
tzcode source: internal

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

other attached packages:
 [1] EnhancedVolcano_1.20.0      ggrepel_0.9.5               ggplot2_3.4.4              
 [4] DESeq2_1.42.0               SummarizedExperiment_1.32.0 Biobase_2.62.0             
 [7] MatrixGenerics_1.14.0       matrixStats_1.2.0           GenomicRanges_1.54.1       
[10] BiocManager_1.30.22         GenomeInfoDb_1.38.6         IRanges_2.36.0             
[13] S4Vectors_0.40.2            BiocGenerics_0.48.1        

loaded via a namespace (and not attached):
 [1] gtable_0.3.4            circlize_0.4.15         shape_1.4.6             xfun_0.42              
 [5] GlobalOptions_0.1.2     lattice_0.22-5          numDeriv_2016.8-1.1     vctrs_0.6.5            
 [9] tools_4.3.2             bitops_1.0-7            generics_0.1.3          parallel_4.3.2         
[13] tibble_3.2.1            fansi_1.0.6             pkgconfig_2.0.3         Matrix_1.6-5           
[17] lifecycle_1.0.4         GenomeInfoDbData_1.2.11 farver_2.1.1            compiler_4.3.2         
[21] munsell_0.5.0           codetools_0.2-19        htmltools_0.5.7         RCurl_1.98-1.14        
[25] yaml_2.3.8              pillar_1.9.0            crayon_1.5.2            MASS_7.3-60.0.1        
[29] BiocParallel_1.36.0     DelayedArray_0.28.0     emdbook_1.3.13          abind_1.4-5            
[33] bdsmatrix_1.3-6         tidyselect_1.2.0        locfit_1.5-9.8          digest_0.6.34          
[37] mvtnorm_1.2-4           dplyr_1.1.4             labeling_0.4.3          fastmap_1.1.1          
[41] grid_4.3.2              colorspace_2.1-0        cli_3.6.2               SparseArray_1.2.4      
[45] magrittr_2.0.3          S4Arrays_1.2.0          utf8_1.2.4              withr_3.0.0            
[49] scales_1.3.0            rmarkdown_2.25          XVector_0.42.0          coda_0.19-4.1          
[53] evaluate_0.23           knitr_1.45              bbmle_1.0.25.1          rlang_1.1.3            
[57] Rcpp_1.0.12             glue_1.7.0              apeglm_1.24.0           rstudioapi_0.15.0      
[61] plyr_1.8.9              R6_2.5.1                zlibbioc_1.48.0        
>

Can this be related to differences in the package versions?

It might, but since you do not know the version, nor show code it is impossible to debug precisely. The general advise is to document code and software version properly so your analysis is reproducible.