Hi there,

I am analysing some RNA expression from an experiment with a set up like:

sample     condition       moment
    R1         A             1     
    R2         A             1    
    R3         A             1     
    R4         A             2     
    R5         A             2     
    R6         A             2  
    C1         B             1     
    C2         B             1    
    C3         B             1     
    C4         B             2     
    C5         B             2     
    C6         B             2

I have compared RNA expression between moments. It is mean : (R1,R2,R3) vs (R4,R5,R6)
and (C1,C2,C3) vs (C4,C5,C6) by doing:

library(DESeq2)
library(tidyverse)

#### Load data
library(readxl)

setwd("~/Documents/path/to/txt/file/")
data= read.table("Expression_level.txt", header = T)
View(data)
                          R1   R2     R3       R4     R5       R6
gene-CpipJ_CPIJ008101 484021 412077 445173  154707  148776  169263
gene-CpipJ_CPIJ001132 334997 391789 435968  445623  504466  445865
gene-CpipJ_CPIJ006209 326414 260289 301946  169859  149214  141446
gene-CpipJ_CPIJ002271 320207 282722 326901  203648  170398  134834
gene-CpipJ_CPIJ005941 316818 252593 273103   55266   43730   26304
gene-CpipJ_CPIJ009303 269236 357244 386633  426546  531801  483546
gene-CpipJ_CPIJ010326 233568 226659 254108  362953  278742  325969
gene-CpipJ_CPIJ008915 230936 276916 277624  355937  357974  239651
gene-CpipJ_CPIJ009571 223388 187980 207711  128457  139515   87437

annotation.info <- read.table("~/Documents//path/to/txt/file/",header = T)

  Viewannotation.info)
  sample     condition       moment
    R1         A             1     
    R2         A             1    
    R3         A             1     
    R4         A             2     
    R5         A             2     
    R6         A             2  

## Create Data Set
dds <- DESeqDataSetFromMatrix(countData = data,
                              colData = annotation.info,
                              design = ~ moment)

#do the analyses
dds <- DESeq(dds)
res <- results(dds)
res

And then I did the same for Condition B ---> res.1

Obviously, the results are different for each analysis:

summary(res) 
out of 18958 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up)       : 2108, 11%
LFC < 0 (down)     : 1873, 9.9%
    outliers [1]       : 2, 0.011%
    low counts [2]     : 2911, 15%
    (mean count < 2)

summary(res.1)
    out of 17783 with nonzero total read count
    adjusted p-value < 0.1
    LFC > 0 (up)       : 4636, 26%
    LFC < 0 (down)     : 5751, 32%
    outliers [1]       : 6, 0.034%
    low counts [2]     : 2039, 11%
    (mean count < 1)

My question is the following: Is there any way of statistically compare these two results? I would like to know which genes are differentially expressed between condition. I would also like to know whether these diferencial expressed genes are up or down regulated. Is it possible?

Thank you so much in advance.