Hi, I don't see any changes in the results (both the number and also in the direction of log2Foldchange) when I shift from treated to untreated as ref and versa. Here are my codes to create metadata for a DESeq object:
Create metadata a DESeq object (ref = "Asymptomatic")
colData <- data.frame(ID=colnames(readMatrix_fc), Sample=rep(c("R29","R30","R31","R32","R33"), each=4), Day=c("Pre-infected","3dpi","7dpi","15dpi")) colData$condition = c(rep("Symptomatic", 8), rep("Asymptomatic", 8), rep("Symptomatic", 4)) colData$condition = relevel(as.factor(colData$condition), ref = "Asymptomatic") colData$Day = factor(colData$Day, levels = c("Pre-infected","3dpi","7dpi","15dpi")) colData$group = factor(paste(colData$condition, "_",colData$Day, sep = "")) kable(colData)
The results are the same when I change ref as (ref = "Symptomatic")
colData <- data.frame(ID=colnames(readMatrix_fc), Sample=rep(c("R29","R30","R31","R32","R33"), each=4), Day=c("Pre-infected","3dpi","7dpi","15dpi")) colData$condition = c(rep("Symptomatic", 8), rep("Asymptomatic", 8), rep("Symptomatic", 4)) colData$condition = relevel(as.factor(colData$condition), ref = "Symptomatic") colData$Day = factor(colData$Day, levels = c("Pre-infected","3dpi","7dpi","15dpi")) colData$group = factor(paste(colData$condition, "_",colData$Day, sep = "")) kable(colData)
sessionInfo( ) R version 4.1.3 (2022-03-10) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 20.04.4 LTS
Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
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
attached base packages: [1] stats4 stats graphics grDevices utils datasets methods [8] base
other attached packages: [1] RColorBrewer_1.1-3 knitr_1.40 [3] DESeq2_1.34.0 SummarizedExperiment_1.24.0 [5] Biobase_2.54.0 MatrixGenerics_1.6.0 [7] matrixStats_0.62.0 GenomicRanges_1.46.1 [9] GenomeInfoDb_1.30.1 IRanges_2.28.0 [11] S4Vectors_0.32.4 BiocGenerics_0.40.0 [13] pheatmap_1.0.12 ggplot2_3.3.6
loaded via a namespace (and not attached): [1] locfit_1.5-9.5 Rcpp_1.0.9 lattice_0.20-45 [4] png_0.1-7 Biostrings_2.62.0 digest_0.6.29 [7] assertthat_0.2.1 utf8_1.2.2 R6_2.5.1 [10] RSQLite_2.2.14 highr_0.9 httr_1.4.4 [13] pillar_1.8.1 zlibbioc_1.40.0 rlang_1.0.5 [16] annotate_1.72.0 blob_1.2.3 Matrix_1.4-1 [19] labeling_0.4.2 splines_4.1.3 BiocParallel_1.28.3 [22] geneplotter_1.72.0 RCurl_1.98-1.7 bit_4.0.4 [25] munsell_0.5.0 DelayedArray_0.20.0 xfun_0.32 [28] compiler_4.1.3 pkgconfig_2.0.3 tidyselect_1.1.2 [31] KEGGREST_1.34.0 tibble_3.1.8 GenomeInfoDbData_1.2.7 [34] XML_3.99-0.10 fansi_1.0.3 crayon_1.5.1 [37] dplyr_1.0.10 withr_2.5.0 bitops_1.0-7 [40] grid_4.1.3 xtable_1.8-4 gtable_0.3.1 [43] lifecycle_1.0.1 DBI_1.1.2 magrittr_2.0.3 [46] scales_1.2.1 cli_3.3.0 cachem_1.0.6 [49] farver_2.1.1 XVector_0.34.0 genefilter_1.76.0 [52] generics_0.1.3 vctrs_0.4.1 tools_4.1.3 [55] bit64_4.0.5 glue_1.6.2 purrr_0.3.4 [58] parallel_4.1.3 fastmap_1.1.0 survival_3.3-1 [61] AnnotationDbi_1.56.2 colorspace_2.0-3 memoise_2.0.1
Thank you in advance,
./Mohammad
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