Design matrix in limma

Question

[Nai]

I have quantile normalized counts, with negative values: The dataset is:

GeneID  2001    2002    2003    2004    2005    2006    2007    2008    2009    2010    2011    2012    2013    2014    2015    2016    
1/2-SBSRNA4     1.84545405543259        0.6665398175808 1.59873554207786        1.89298926465623        1.26568208427265        1.88410700890907        1.74378606410793        1.48987360722618        
A1BG    1.6165355686345 2.68681326811308        1.50663367983524        2.25377918290859        2.67375515222443        2.37256130394363        2.98553798816952        2.7872063927308 2.46972065233526 
A1BG-AS1        0.0318256718292522      1.06223446343374        0.365739932809055       0.160454525989031       -0.189562119063132      0.451464743899586       1.00348737045778        0.521080706070493 
A2LD1   2.42805396344275        3.29182280645954        3.42740052556388        3.54573585005455        2.6718279086933 2.84892844820465        3.23788385068264        2.5512302536277 3.00143277095887   
A2M     8.69286445805741        9.01321493190288        9.06178519781115        9.37509171855292        9.15365897313587        10.225835039655 9.58498357891138        9.26308027293732        10.10798379

This data set has zeros. I have no idea about the comparisons between samples. I am new in limma

Kindly help me

[Basti]

There are many tutorials available online for such analysis, I think it is important to have a look at them before asking such question : https://www.bioconductor.org/packages/devel/bioc/vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf If you have specific question, we would be likely to help, but all the information you need is in the tutorial

[Nai]

Dear Basti,

Thank you for your response. I think , my question is pretty clear about limma and normalized count matrix. In my knowledge, EdgeR never use pre-normalized count matrix, it is prefered to use with raw count matrix as deseq2 (https://support.bioconductor.org/p/65890/#65891)