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DEseq matrix preparation

I recently had a question related to having data as integer for DEseq .

One data looks like this will have no problem

> head(df)
  treat treat1 treat2 ctrl ctrl1 ctrl2
1    95     91     88   67    65    84
2    83     97     90   88    85    89
3    99    103     99   73    83    82
4    82     99     94   82    62    72
5    88     90     96   87    61    86
6    92    101     80   74    66    62

but a data like this one will have a problem

head(df2) 
            treat   treat1   treat2  ctrl  ctrl1 ctrl2
    1    0.95    0. 91    0. 88  0. 67   0. 65   0. 84
    2   0. 83    0. 97    0. 90   0.88   0. 85   0. 89
    3    0.99    0.103     0.99  0.73   0. 83    0.82
    4    0.82     0.99    0. 94  0. 82   0. 62    0.72
    5    0.88     0.90    0.96   0.87    0.61    0.86
    6    0.92    0.101     0.80   0.74    0.66    0.62

Do you think if I just normalised the data to above , is OK? is there any other way to do it ?

if I don't do the normalisation, is there any other way ? or any other package ?

deseq r

The question you need to ask yourself is, "regardless of how I transform my data, is the resulting analysis appropriate?" If the answer to that is, "yes!", then go ahead and "normalize" (transform) the data.

@Devon Ryan for sure, but imagine if we make integer the df2, I will get all of them zero. which kind of normalisation would you use ?

There's no generic answer to that. One first needs to know what the numbers represent. It may not be possible to convert them into a form where using DESeq2 (or equivalent) would be appropriate.

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