Hello! I am having a difficult time with the design element of my Deseq2 timecourse following the vignette in (Love MI, Anders S, Kim V and Huber W. RNA-Seq workflow: gene-level exploratory analysis and differential expression [version 1; referees: 2 approved]. F1000Research 2015, 4:1070 (doi: 10.12688/f1000research.7035.1)) as a template.

My experiment is looking at Controls (wild type mice) Vs Experimental (knock out) with 4 biological replicates each, at 4 time points (p0, p7, p15, p30) These are not repeated measures on the same group of mice (each mouse was sac'ed at each timepoint). My hope is to look at condition specific differences over time. Here is what I have so far:

sampleFiles<- c("CB-1712-P0-M-KO.counts.processed.txt",
                "CB-1713-P0-M-WT.counts.processed.txt",
                "CB-1741-P0-M-WT.counts.processed.txt",
                "CB-1620-P0-M-WT.counts.processed.txt",
                "CB-1650-P0-M-KO.counts.processed.txt",
                "CB-1700-P0-M-WT.counts.processed.txt",
                "CB-1702-P0-M-KO.counts.processed.txt",
                "CB-1704-P0-M-KO.counts.processed.txt",
                "CB-1171-P7-M-WT.counts.processed.txt",
                "CB-1185-P7-M-KO.counts.processed.txt",
                "CB-1191-P7-M-KO.counts.processed.txt",
                "CB-1330-P7-M-WT.counts.processed.txt",
                "CB-1370-P7-M-WT.counts.processed.txt",
                "CB-1380-P7-M-WT.counts.processed.txt",
                "CB-1381-P7-M-KO.counts.processed.txt",
                "CB-1414-P7-M-KO.counts.processed.txt",
                "CB-1547-P15-M-WT.counts.processed.txt",
                "CB-1210-P15-M-KO.counts.processed.txt",
                "CB-1220-P15-M-WT.counts.processed.txt",
                "CB-1223-P15-M-KO.counts.processed.txt",
                "CB-1231-P15-M-KO.counts.processed.txt",
                "CB-1233-P15-M-WT.counts.processed.txt",
                "CB-1540-P15-M-KO.counts.processed.txt",
                "CB-1542-P15-M-WT.counts.processed.txt",
                "CB-CM847-P30-M-WT.counts.processed.txt",
                "CB-1255-P30-M-KO.counts.processed.txt",
                "CB-1265-P30-M-WT.counts.processed.txt",
                "CB-1266-P30-M-KO.counts.processed.txt",
                "CB-1341-P30-M-KO.counts.processed.txt",
                "CB-CM838-P30-M-WT.counts.processed.txt",
                "CB-CM839-P30-M-KO.counts.processed.txt",
                "CB-CM846-P30-M-WT.counts.processed.txt")

sampleNames <- c("CB-1712-P0-M-KO",
                 "CB-1713-P0-M-WT",
                 "CB-1741-P0-M-WT",
                 "CB-1620-P0-M-WT",
                 "CB-1650-P0-M-KO",
                 "CB-1700-P0-M-WT",
                 "CB-1702-P0-M-KO",
                 "CB-1704-P0-M-KO",
                 "CB-1171-P7-M-WT",
                 "CB-1185-P7-M-KO",
                 "CB-1191-P7-M-KO",
                 "CB-1330-P7-M-WT",
                 "CB-1370-P7-M-WT",
                 "CB-1380-P7-M-WT",
                 "CB-1381-P7-M-KO",
                 "CB-1414-P7-M-KO",
                 "CB-1547-P15-M-WT",
                 "CB-1210-P15-M-KO",
                 "CB-1220-P15-M-WT",
                 "CB-1223-P15-M-KO",
                 "CB-1231-P15-M-KO",
                 "CB-1233-P15-M-WT",
                 "CB-1540-P15-M-KO",
                 "CB-1542-P15-M-WT",
                 "CB-CM847-P30-M-WT",
                 "CB-1255-P30-M-KO",
                 "CB-1265-P30-M-WT",
                 "CB-1266-P30-M-KO",
                 "CB-1341-P30-M-KO",
                 "CB-CM838-P30-M-WT",
                 "CB-CM839-P30-M-KO",
                 "CB-CM846-P30-M-WT")



Genotype <- c("Exp","Control","Control","Control","Exp",
                     "Control","Exp","Exp","Control","Exp","Exp","Control",
                     "Control","Control","Exp","Exp","Control","Exp",
                     "Control","Exp","Exp","Control","Exp","Control",
                     "Control","Exp","Control","Exp","Exp","Control",
                     "Exp","Control")
time<- c("0","0","0","0","0","0","0","0","7","7","7","7","7","7","7","7",
          "15","15","15","15","15","15","15","15",
          "30","30","30","30","30","30","30","30")



sampleTable<-data.frame(sampleName=sampleNames, fileName=sampleFiles, condition=Genotype, time=time)

ddsHTSeq<-DESeqDataSetFromHTSeqCount(sampleTable=sampleTable, directory=directory, design=~ condition + time + condition:time)
nrow(ddsHTSeq)
keep <- rowSums(counts(ddsHTSeq)) > 10
dds <- ddsHTSeq[keep,]
nrow(dds)

dds$condition <- relevel(dds$condition, ref = "Control")
ddsTC <- DESeq(dds, test="LRT", reduced = ~ condition + time)
resTC <- results(ddsTC)
resTC$symbol <- mcols(ddsTC)$symbol
head(resTC[order(resTC$padj),],4)
resultsNames(ddsTC)


"Intercept"     "condition_Exp_vs_Control" "time_15_vs_0"            
[4] "time_30_vs_0"             "time_7_vs_0"              "conditionExp.time15"     
[7] "conditionExp.time30"      "conditionExp.time7"

This seems to not be comparing what I want it to. I would like it to compare controls vs exp with time as an interaction term but it seems that it is not grouping the analysis the way I would like. Any help would be greatly appreciated!

"I would like it to compare controls vs exp with time as an interaction term but it seems that it is not grouping the analysis the way I would like"

It looks correct to me, so I think if the terms are unfamiliar, you should collaborate with a local statistician to help with the interpretation of results. I unfortunately don't have sufficient time to provide statistical design or interpretation support here, but I have to reserve my time only for software support.