results1 <- results( dds, contrast=c("combined","B_treated","B_untreated") ) results2 <- results( dds, contrast=c("combined","B_treated","B_untreated"), lfcThreshold=0.58496 ) summary(results1) summary(results2)
Output. The results are different but they both say "LFC > 0 (up)" and "LFC < 0 (down)":
> summary(results1) adjusted p-value < 0.1 LFC > 0 (up) : 1548, 3.7% LFC < 0 (down) : 2116, 5% outliers [1] : 24, 0.057% low counts [2] : 24080, 57% (mean count < 19)
> summary(results2) adjusted p-value < 0.1 LFC > 0 (up) : 42, 0.1% LFC < 0 (down) : 25, 0.06% outliers [1] : 24, 0.057% low counts [2] : 20071, 48% (mean count < 6)
A second question. When I look at the list of genes from results1 there are 775 significantly increased and with log2fc > 0.58496 and 924 significantly decreased log2fs < 0.58496, yet from results2 the numbers are much lower. Does this seem right?
> sessionInfo() R version 3.4.3 (2017-11-30) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 14393) Matrix products: default locale: [1] LC_COLLATE=English_Canada.1252 LC_CTYPE=English_Canada.1252 LC_MONETARY=English_Canada.1252 [4] LC_NUMERIC=C LC_TIME=English_Canada.1252 attached base packages: [1] grid parallel stats4 stats graphics grDevices utils datasets methods [10] base other attached packages: [1] biomaRt_2.34.2 ggbeeswarm_0.6.0 ggrepel_0.7.0 [4] extrafont_0.17 ggplot2_2.2.1 PoiClaClu_1.0.2 [7] RColorBrewer_1.1-2 pheatmap_1.0.8 DESeq2_1.18.1 [10] SummarizedExperiment_1.8.1 DelayedArray_0.4.1 matrixStats_0.53.1 [13] Biobase_2.38.0 GenomicRanges_1.30.0 GenomeInfoDb_1.14.0 [16] IRanges_2.12.0 S4Vectors_0.16.0 BiocGenerics_0.24.0 loaded via a namespace (and not attached): [1] httr_1.3.1 RMySQL_0.10.13 bit64_0.9-7 [4] splines_3.4.3 Formula_1.2-2 assertthat_0.2.0 [7] latticeExtra_0.6-28 blob_1.1.0 vipor_0.4.5 [10] GenomeInfoDbData_1.0.0 Rsamtools_1.30.0 progress_1.1.2 [13] Rttf2pt1_1.3.5 pillar_1.1.0 RSQLite_2.0 [16] backports_1.1.2 lattice_0.20-35 extrafontdb_1.0 [19] digest_0.6.15 XVector_0.18.0 checkmate_1.8.5 [22] colorspace_1.3-2 htmltools_0.3.6 Matrix_1.2-12 [25] plyr_1.8.4 XML_3.98-1.10 genefilter_1.60.0 [28] zlibbioc_1.24.0 xtable_1.8-2 scales_0.5.0 [31] BiocParallel_1.12.0 htmlTable_1.11.2 tibble_1.4.2 [34] annotate_1.56.1 GenomicFeatures_1.30.3 nnet_7.3-12 [37] lazyeval_0.2.1 survival_2.41-3 magrittr_1.5 [40] memoise_1.1.0 foreign_0.8-69 beeswarm_0.2.3 [43] tools_3.4.3 data.table_1.10.4-3 prettyunits_1.0.2 [46] stringr_1.3.0 munsell_0.4.3 locfit_1.5-9.1 [49] cluster_2.0.6 AnnotationDbi_1.40.0 Biostrings_2.46.0 [52] compiler_3.4.3 rlang_0.2.0 RCurl_1.95-4.10 [55] rstudioapi_0.7 htmlwidgets_1.0 bitops_1.0-6 [58] base64enc_0.1-3 gtable_0.2.0 curl_3.1 [61] DBI_0.7 R6_2.2.2 GenomicAlignments_1.14.1 [64] gridExtra_2.3 rtracklayer_1.38.3 knitr_1.20 [67] bit_1.1-12 Hmisc_4.1-1 stringi_1.1.6 [70] Rcpp_0.12.15 geneplotter_1.56.0 rpart_4.1-12 [73] acepack_1.4.1
By the way, I just fixed this in devel (so released in April 2018) so that it shows the LFC threshold value: