Hi Michael,

I am trying to use the DESseq package to estimate ribosome loading efficiency as described in "systemPipeR Workflow for Ribo-Seq and polyRibo-Seq Experiments".

But I have run into some problems that I can't understand the genesis i.e.

"Error in nbinomLRT(object, full = full, reduced = reduced, betaPrior = betaPrior,  :

less than one degree of freedom, perhaps full and reduced models are not in the correct order"

I have tried to look around the source of this error in the manpages but can't find it. 

My colData looks like this:

DataFrame with 8 rows and 2 columns

              assay condition

           <factor>  <factor>

M1A     Ribo        M1

M1B     Ribo        M1

A1A      Ribo        A1

A1B      Ribo        A1

V1A     mRNA        M1

V1B    mRNA        M1

M6A     mRNA        A1

M6B     mRNA        A1

with a datafile matching the colData row.names and as you can see every sample has a df>1

But when I run:

dds=DESeq(dds,test="LRT",reduced= ~assay+condition)

I get the above error message.

Is there something am missing?

Thanks,

Musa

hi Musa,

What is the design you used when creating the dds? You should read over the "Likelihood ratio test section" of the vignette

vignette("DESeq2")

and this help page which explains how the LRT works in DESeq2:

?nbinomLRT

You don't have to use the nbinomLRT() function directly, it is used within DESeq(), but this is where we have the help information.

Hi Michael,

Thanks for your response

This is how I created the dds

dds=DESeqDataSetFromMatrix(countData=as.matrix(y[,rownames(coldata)]),colData=coldata,design=~assay+condition:condition)

with coldata as is in the email above.

I have looked at the vignette but can't figure out the source or what likely causes this type of error.

Musa