Hi

I have a phenotype of my interest (T versus C). My samples have been collected in several runs(batches).

PCA shows that runs can separate my samples

This is how my colData looks

> pData3[,c(1,2,8)]
    Bacth_no Samp_no StatuS
s1   Batch4      36      T
s2   Batch4      37      T
s3   Batch5      43      C
s4   Batch5      44      C
s5   Batch5      47      C
s6   Batch5      48      C
s7   Batch6      53      C
s8   Batch6      54      C
> 

I am trying these to remove the run effects but I get error

 >  dds <- DESeqDataSetFromMatrix(countData = exprs_df[ , rownames(pData3)],
    +                                                                colData = pData3,
    +                                                                design = ~ Bacth_no+Status)
Error in checkFullRank(modelMatrix) : 
  the model matrix is not full rank, so the model cannot be fit as specified.
  One or more variables or interaction terms in the design formula are linear
  combinations of the others and must be removed.

  Please read the vignette section 'Model matrix not full rank':

  vignette('DESeq2')
In addition: Warning message:
In DESeqDataSet(se, design = design, ignoreRank) :
  some variables in design formula are characters, converting to factors




 >  dds <- DESeqDataSetFromMatrix(countData = exprs_df[ , rownames(pData3)],
    +                                                                colData = pData3,
    +                                                                design = ~ Bacth_no+Status+Bacth_no:Status)
Error in checkFullRank(modelMatrix) : 
  the model matrix is not full rank, so the model cannot be fit as specified.
  One or more variables or interaction terms in the design formula are linear
  combinations of the others and must be removed.

  Please read the vignette section 'Model matrix not full rank':

  vignette('DESeq2')
In addition: Warning message:
In DESeqDataSet(se, design = design, ignoreRank) :
  some variables in design formula are characters, converting to factors
>

Please could you tell me a helpful design?

Thanks a million

Batch 4 is nested with Status T, all you can technically do is ~Status or ~Batch. If you want to do that is on you, the support site is not meant to guide through individual analysis.

See vignette where this is explained: http://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#linear-combinations