[BioC] results interpretation
Leonardo Pitombo [guest]
guest at bioconductor.org
Tue Mar 4 17:44:30 CET 2014
Dear Dr. Michael,
Iâm using DESeq2 to compare data from different treatments to find possible bioindicators. I applied the DESeq function by two ways:
A) treatmentdeseq <- phyloseq_to_deseq2(biom_otu_tax, ~treatment)
B) treatmentdeseq2<- phyloseq_to_deseq2(biom_otu_tax, ~treatment + condition x)
The intercept in both is the same, but the comparisons among treatments are (a bit) different when I call A and B. In B, does the condition exert some influence on analysis comparing treatments?
Could you explain why?
Thanks,
Leonardo M. Pitombo
-- output of sessionInfo():
> sessionInfo("DESeq2")
R version 3.0.1 (2013-05-16)
Platform: x86_64-w64-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=Dutch_Netherlands.1252 LC_CTYPE=Dutch_Netherlands.1252 LC_MONETARY=Dutch_Netherlands.1252
[4] LC_NUMERIC=C LC_TIME=Dutch_Netherlands.1252
attached base packages:
character(0)
other attached packages:
[1] DESeq2_1.2.10
loaded via a namespace (and not attached):
[1] ade4_1.6-2 annotate_1.40.0 AnnotationDbi_1.24.0 ape_3.0-11
[5] base_3.0.1 Biobase_2.22.0 BiocGenerics_0.8.0 biom_0.3.11
[9] Biostrings_2.30.1 cluster_1.14.4 codetools_0.2-8 colorspace_1.2-4
[13] datasets_3.0.1 DBI_0.2-7 dichromat_2.0-0 digest_0.6.4
[17] foreach_1.4.1 genefilter_1.44.0 GenomicRanges_1.14.4 ggplot2_0.9.3.1
[21] glmmADMB_0.7.7 graphics_3.0.1 grDevices_3.0.1 grid_3.0.1
[25] gtable_0.1.2 igraph_0.7.0 IRanges_1.20.6 iterators_1.0.6
[29] labeling_0.2 lattice_0.20-24 locfit_1.5-9.1 MASS_7.3-29
[33] Matrix_1.1-2 methods_3.0.1 multtest_2.18.0 MuMIn_1.9.13
[37] munsell_0.4.2 nlme_3.1-113 parallel_3.0.1 permute_0.8-3
[41] phyloseq_1.7.12 plyr_1.8 proto_0.3-10 R2admb_0.7.10
[45] RColorBrewer_1.0-5 Rcpp_0.11.0 RcppArmadillo_0.4.000.2 reshape2_1.2.2
[49] RJSONIO_1.0-3 RSQLite_0.11.4 scales_0.2.3 splines_3.0.1
[53] stats_3.0.1 stats4_3.0.1 stringr_0.6.2 survival_2.37-7
[57] tools_3.0.1 utils_3.0.1 vegan_2.0-10 XML_3.98-1.1
[61] xtable_1.7-1 XVector_0.2.0
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