[BioC] DESeqs two-factor two-level, interaction is interested

Michael Love michaelisaiahlove at gmail.com
Sat May 17 16:58:43 CEST 2014


hi Shawn,


On Sat, May 17, 2014 at 2:00 AM, Shawn [guest] <guest at bioconductor.org> wrote:
> Hello Mike,
>
> Please allow me ask a basic question.  What does 'log2FoldChange' in the results of  DESeq2 analysis really mean for the interaction of a two-factor two-level design?

The meaning is the same as for other linear models. The interaction
term for the generalized linear model tests if the effect of both day
and treatment is not simply multiplicative (or additive in the log2
space). If this term is significantly non-zero (the default test in
DESeq2), then being in the group: (day=B and treatment=treat) is not
simply the product of the day=B fold change and the treatment=treat
fold change.


> Is it possible to compare 'Factor A level 1' to ' Factor A level 2' or other similar comparison?

For example, the day B over A effect:

results(dds, contrast=c("day","B","A"))

or equivalently

results(dds, name="day_B_vs_A")

Check the help for ?results for more examples.

Mike

>
> Here are the part of codes I used:
>
>
> dds <- phyloseq_to_deseq2(phyloseq.obj, design=~ Treatment*Day)
>
> colData(dds)$Treatment<- factor(colData(dds)$Treatment,levels=c("Control","Treat"));
> colData(dds)$Day<- factor(colData(dds)$Day,levels=c("A","B"))
>
> dds$Treatment<- relevel(dds$Treatment, "Control")
> dds$Day<- relevel(dds$Day, "A")
>
> dds <- DESeq(dds, fitType="local",betaPrior=FALSE)
>
> Shawn
>
>
>  -- output of sessionInfo():
>
> sessionInfo()
> R version 3.1.0 (2014-04-10)
> Platform: x86_64-apple-darwin13.1.0 (64-bit)
>
> locale:
> [1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8
>
> attached base packages:
>  [1] parallel  grid      splines   stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
>  [1] ecodist_1.2.9           Biostrings_2.32.0       doParallel_1.0.8        foreach_1.4.2
>  [5] iterators_1.0.7         metagenomeSeq_1.6.0     gplots_2.13.0           limma_3.20.1
>  [9] Biobase_2.24.0          DESeq2_1.4.5            GenomicRanges_1.16.3    GenomeInfoDb_1.0.2
> [13] RcppArmadillo_0.4.300.0 Rcpp_0.11.1             XVector_0.4.0           IRanges_1.22.6
> [17] BiocGenerics_0.10.0     locfit_1.5-9.1          phangorn_1.99-7         genefilter_1.46.1
> [21] adephylo_1.1-6          scatterplot3d_0.3-35    analogue_0.12-0         rgl_0.93.996
> [25] princurve_1.1-12        labdsv_1.6-1            mgcv_1.7-29             indicspecies_1.7.1
> [29] biom_0.3.13             ggplot2_0.9.3.1         plyr_1.8.1              phyloseq_1.9.2
> [33] pamr_1.54.1             cluster_1.15.2          survival_2.37-7         vegan_2.0-10
> [37] lattice_0.20-29         permute_0.8-3           RColorBrewer_1.0-5      matrixStats_0.8.14
> [41] MASS_7.3-33             ape_3.1-1               ade4_1.6-2              nlme_3.1-117
>
> loaded via a namespace (and not attached):
>  [1] adegenet_1.4-1       annotate_1.42.0      AnnotationDbi_1.26.0 bitops_1.0-6
>  [5] brglm_0.5-9          caTools_1.17         codetools_0.2-8      colorspace_1.2-4
>  [9] data.table_1.9.2     DBI_0.2-7            digest_0.6.4         fastmatch_1.0-4
> [13] gdata_2.13.3         geneplotter_1.42.0   gtable_0.1.2         gtools_3.4.0
> [17] httpuv_1.3.0         igraph_0.7.0         KernSmooth_2.23-12   Matrix_1.1-3
> [21] multtest_2.20.0      munsell_0.4.2        phylobase_0.6.8      proto_0.3-10
> [25] R.methodsS3_1.6.1    reshape2_1.4         RJSONIO_1.2-0.2      RSQLite_0.11.4
> [29] scales_0.2.4         shiny_0.9.1          stats4_3.1.0         stringr_0.6.2
> [33] tools_3.1.0          XML_3.98-1.1         xtable_1.7-3         zlibbioc_1.10.0
>
>
> --
> Sent via the guest posting facility at bioconductor.org.



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