My issue is that DESeq no longer works and does not give me the correct contrast options. This was working before I updated to DESeq2 1.22.2
Here is my code:
> line.ds <- phyloseq_to_deseq2(ps.phyla, ~ Line) > diagdds <- DESeq(line.ds, test="Wald", fitType="parametric") using pre-existing size factors estimating dispersions found already estimated dispersions, replacing these gene-wise dispersion estimates mean-dispersion relationship final dispersion estimates fitting model and testing > resultsNames(diagdds)  "Intercept" "Line1" "Line2" "Line3" "Line4"
I'll also show some of the data included in my DESeq object
> line.ds@design ~Line > line.ds@colData DataFrame with 40 rows and 9 columns X Genotype Block Line Wavelength Time <factor> <integer> <integer> <factor> <numeric> <factor> 1 1 4 1 N321 0.169 After 10 10 2 2 N326 0.114 After 11 11 2 3 N326 0.137 After 12 12 2 4 N326 0.092 After 13 13 5 1 N336 0.423 After
Now, what I would see before I updated was something like this: N331, N326, N337 etc. that matched the 5 factor levels in "Line".
I can perform the above analysis using a continuous variable with no trouble but do have issues when I group the samples into categories.
platform x86_64-apple-darwin15.6.0 arch x86_64 os darwin15.6.0 system x86_64, darwin15.6.0 status major 3 minor 5.1 year 2018 month 07 day 02 svn rev 74947 language R version.string R version 3.5.1 (2018-07-02) nickname Feather Spray
I have found that other people have posted similar questions regarding a change to the most up-to-date DESeq package but I have not been able to fix my problem based on the responses to others posts. Hence, why I am posting here.
Any help would be greatly appreciated! Thanks!