1 DESeq2 withouth removing unwanted variation
dds <- DESeqDataSetFromMatrix(countData = counts_table,
colData = design_df,
design = ~ condition)
keep <- rowSums(counts(dds)) >= 10
dds <- dds[keep,]
dds <- DESeq(dds)1.1 MA-plots
The threshold used for a dot to be coloured in blue in the MA-plots is: p-value adjusted < 0.05.
Very few Differentially Expressed Genes.
2 Accounting for unwanted variation computed by RUVs in DESeq2 design formula
# merging design_df with phenoData from RUVs, which contains the factor of unwanted variation
pData(ses3)$sample <- rownames(pData(ses3))
design_df <- merge(design_df, pData(ses3)[, c("sample", grep("W_", colnames(pData(ses3)), value = TRUE))], by = "sample", all = FALSE)
rownames(design_df) <- design_df$sample
counts_table <- counts_table[, rownames(design_df)]# creating DESeqDataset
dds_RUVs <- DESeqDataSetFromMatrix(countData = counts_table,
colData = design_df,
design = ~ W_1 + W_2 + W_3 + condition)
# pre-filtering low count genes
keep <- rowSums(counts(dds_RUVs)) >= 10
dds_RUVs <- dds_RUVs[keep,]
# the standard differential expression analysis steps are wrapped into a single function, DESeq
dds_RUVs <- DESeq(dds_RUVs)
# DESeq results
res_all_RUVs <- get_results_all_comp(dds_RUVs)2.1 MA-plots
2.1.1 FIGURE
I export the DE genes to ../../analysis/DESeq/RUVs/.
sessionInfo()## R version 4.1.3 (2022-03-10)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.6 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=it_IT.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=it_IT.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=it_IT.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=it_IT.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] dplyr_1.0.10 RUVSeq_1.28.0
## [3] edgeR_3.36.0 limma_3.50.3
## [5] EDASeq_2.28.0 ShortRead_1.52.0
## [7] GenomicAlignments_1.30.0 Rsamtools_2.10.0
## [9] Biostrings_2.62.0 XVector_0.34.0
## [11] BiocParallel_1.28.3 vsn_3.62.0
## [13] ggrepel_0.9.2 pheatmap_1.0.12
## [15] gridExtra_2.3 ggpubr_0.5.0
## [17] DESeq2_1.34.0 SummarizedExperiment_1.24.0
## [19] Biobase_2.54.0 MatrixGenerics_1.6.0
## [21] matrixStats_0.62.0 GenomicRanges_1.46.1
## [23] GenomeInfoDb_1.30.1 IRanges_2.28.0
## [25] S4Vectors_0.32.4 BiocGenerics_0.40.0
## [27] data.table_1.14.6 reshape2_1.4.4
## [29] ggplot2_3.4.0
##
## loaded via a namespace (and not attached):
## [1] backports_1.4.1 aroma.light_3.24.0 BiocFileCache_2.2.1
## [4] plyr_1.8.8 splines_4.1.3 digest_0.6.30
## [7] invgamma_1.1 htmltools_0.5.3 SQUAREM_2021.1
## [10] fansi_1.0.3 magrittr_2.0.3 memoise_2.0.1
## [13] annotate_1.72.0 R.utils_2.12.2 prettyunits_1.1.1
## [16] jpeg_0.1-9 colorspace_2.0-3 blob_1.2.3
## [19] rappdirs_0.3.3 xfun_0.35 crayon_1.5.2
## [22] RCurl_1.98-1.9 jsonlite_1.8.3 genefilter_1.76.0
## [25] survival_3.2-13 glue_1.6.2 gtable_0.3.1
## [28] zlibbioc_1.40.0 DelayedArray_0.20.0 car_3.1-1
## [31] abind_1.4-5 scales_1.2.1 DBI_1.1.3
## [34] rstatix_0.7.1 Rcpp_1.0.9 xtable_1.8-4
## [37] progress_1.2.2 bit_4.0.5 preprocessCore_1.56.0
## [40] truncnorm_1.0-8 httr_1.4.4 RColorBrewer_1.1-3
## [43] ellipsis_0.3.2 farver_2.1.1 pkgconfig_2.0.3
## [46] XML_3.99-0.12 R.methodsS3_1.8.2 sass_0.4.2
## [49] dbplyr_2.2.1 deldir_1.0-6 locfit_1.5-9.6
## [52] utf8_1.2.2 tidyselect_1.2.0 labeling_0.4.2
## [55] rlang_1.0.6 AnnotationDbi_1.56.2 munsell_0.5.0
## [58] tools_4.1.3 cachem_1.0.6 cli_3.4.1
## [61] generics_0.1.3 RSQLite_2.2.18 broom_1.0.1
## [64] evaluate_0.18 stringr_1.4.1 fastmap_1.1.0
## [67] yaml_2.3.6 knitr_1.40 bit64_4.0.5
## [70] purrr_0.3.5 KEGGREST_1.34.0 R.oo_1.25.0
## [73] xml2_1.3.3 biomaRt_2.50.3 compiler_4.1.3
## [76] rstudioapi_0.14 filelock_1.0.2 curl_4.3.3
## [79] png_0.1-7 affyio_1.64.0 ggsignif_0.6.4
## [82] tibble_3.1.8 geneplotter_1.72.0 bslib_0.4.1
## [85] stringi_1.7.8 highr_0.9 GenomicFeatures_1.46.5
## [88] lattice_0.20-45 Matrix_1.5-3 vctrs_0.5.1
## [91] pillar_1.8.1 lifecycle_1.0.3 BiocManager_1.30.22
## [94] jquerylib_0.1.4 irlba_2.3.5.1 bitops_1.0-7
## [97] rtracklayer_1.54.0 R6_2.5.1 BiocIO_1.4.0
## [100] latticeExtra_0.6-30 affy_1.72.0 hwriter_1.3.2.1
## [103] codetools_0.2-18 MASS_7.3-55 assertthat_0.2.1
## [106] rjson_0.2.21 withr_2.5.0 GenomeInfoDbData_1.2.7
## [109] parallel_4.1.3 hms_1.1.2 grid_4.1.3
## [112] prettydoc_0.4.1 tidyr_1.2.1 rmarkdown_2.18
## [115] ashr_2.2-54 carData_3.0-5 mixsqp_0.3-48
## [118] interp_1.1-3 restfulr_0.0.15