On 02.01.2017, I ran an analysis with DESeq2. I ran a similar analysis recently. I used the same input data for both runs! Please see "raw reads" in the excel file (https://www.dropbox.com/s/g7fyqvn1chdnesh/deseq2_bugreport_23102017.xlsx?dl=0). Even tough the normalized reads and basemean are same in both runs, the log2FoldChange, padj, etc are completely different. Moreover, I think there are two bugs:
In the previous one ( I do not have a session info for that, ran on 02.01.2017), for "gene21828" the log2FoldChange is calculated wrongly!
In the new one; for "gene23073","gene8822", the log2FoldChange is calculated wrongly or in another words: even though the reads number are blow 30 reads, the log2FoldChange and padj values are calculated as significantly expressed genes. (see gene8822).
Especially the number of DE genes in the new run is over 600 genes [abs(log2FoldChange) >= 1.0]. In the previous one [abs(log2FoldChange) >= 1.0], it is around 30 genes. 20 fold differences in the number of DE genes!
I could not find anything that I may doing wrong, that is why I am posting.
p.s. : I have a pipeline for RNASeq data analysis that is why there are several packages, such as goseq, GOStats, topGO, ...
> sessionInfo() R version 3.4.1 (2017-06-30) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows >= 8 x64 (build 9200) Matrix products: default locale:  LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252  LC_NUMERIC=C LC_TIME=English_United States.1252 attached base packages:  grid stats4 parallel stats graphics grDevices utils datasets methods base other attached packages:  org.Mm.eg.db_3.4.1 xtable_1.8-2 WriteXLS_4.0.0 stringr_1.2.0  statmod_1.4.30 scales_0.5.0 splitstackshape_1.4.2 Rgraphviz_2.20.0  reshape2_1.4.2 topGO_2.28.0 SparseM_1.77 ReportingTools_2.16.0  knitr_1.17 RColorBrewer_1.1-2 png_0.1-7 plotrix_3.6-6  PerformanceAnalytics_1.4.3541 xts_0.10-0 zoo_1.8-0 pathview_1.16.5  org.Hs.eg.db_3.4.1 pheatmap_1.0.8 org.Dr.eg.db_3.4.1 LSD_3.0  KEGGREST_1.16.1 KEGG.db_3.2.3 GSEABase_1.38.1 gdata_2.18.0  gplots_3.0.1 GOstats_2.42.0 graph_1.54.0 Category_2.42.1  Matrix_1.2-10 goseq_1.28.0 BiasedUrn_1.07 GO.db_3.4.1  ggrepel_0.6.5 ggplot2_2.2.1 GenomicFeatures_1.28.4 geneplotter_1.54.0  annotate_1.54.0 XML_3.98-1.9 lattice_0.20-35 geneLenDataBase_1.12.0  genefilter_1.58.1 fdrtool_1.2.15 edgeR_3.18.1 limma_3.32.5  dtplyr_0.0.2 plyr_1.8.4 DESeq2_1.16.1 SummarizedExperiment_1.6.3  DelayedArray_0.2.7 matrixStats_0.52.2 GenomicRanges_1.28.4 GenomeInfoDb_1.12.2  data.table_1.10.4 calibrate_1.7.2 MASS_7.3-47 biomaRt_2.32.1  BiocParallel_1.10.1 AnnotationForge_1.18.2 AnnotationDbi_1.38.2 IRanges_2.10.3  S4Vectors_0.14.3 Biobase_2.36.2 BiocGenerics_0.22.0 BiocInstaller_1.26.1 loaded via a namespace (and not attached):  backports_1.1.0 Hmisc_4.0-3 AnnotationHub_2.8.2 lazyeval_0.2.0  splines_3.4.1 digest_0.6.12 ensembldb_2.0.4 htmltools_0.3.6  magrittr_1.5 checkmate_1.8.3 memoise_1.1.0 BSgenome_1.44.1  cluster_2.0.6 Biostrings_2.44.2 R.utils_2.5.0 ggbio_1.24.1  colorspace_1.3-2 blob_1.1.0 dplyr_0.7.2 RCurl_1.95-4.8  bindr_0.1 survival_2.41-3 VariantAnnotation_1.22.3 glue_1.1.1  gtable_0.2.0 zlibbioc_1.22.0 XVector_0.16.0 DBI_0.7  GGally_1.3.2 Rcpp_0.12.12 htmlTable_1.9 foreign_0.8-69  bit_1.1-12 OrganismDbi_1.18.0 Formula_1.2-2 htmlwidgets_0.9  httr_1.3.1 acepack_1.4.1 R.methodsS3_1.7.1 pkgconfig_2.0.1  reshape_0.8.7 nnet_7.3-12 locfit_1.5-9.1 rlang_0.1.2  munsell_0.4.3 tools_3.4.1 RSQLite_2.0 yaml_2.1.14  bit64_0.9-7 caTools_1.17.1 AnnotationFilter_1.0.0 bindrcpp_0.2  RBGL_1.52.0 nlme_3.1-131 mime_0.5 R.oo_1.21.0  KEGGgraph_1.38.1 compiler_3.4.1 curl_2.8.1 interactiveDisplayBase_1.14.0  PFAM.db_3.4.1 tibble_1.3.4 stringi_1.1.5 ProtGenerics_1.8.0  bitops_1.0-6 httpuv_1.3.5 rtracklayer_1.36.4 hwriter_1.3.2  R6_2.2.2 latticeExtra_0.6-28 KernSmooth_2.23-15 gridExtra_2.2.1  dichromat_2.0-0 gtools_3.5.0 assertthat_0.2.0 GenomicAlignments_1.12.2  Rsamtools_1.28.0 GenomeInfoDbData_0.99.0 mgcv_1.8-17 rpart_4.1-11  biovizBase_1.24.0 shiny_1.0.5 base64enc_0.1-3