Hi Mike,
Thanks for explaining more.  I am used to working with rarefied microbial
datasets, that is why.  Instead of rarefying I would like to use the DESeq
method.

How would you then suggest going about calculating bray-curtis distance, or
summarized taxa diagrams with these new transformed matrices with negative
values?
Thanks again,
Sophie


On Mon, Apr 14, 2014 at 7:17 AM, Michael Love
<michaelisaiahlove@gmail.com>wrote:

> hi Sophie,
>
> Can you explain why you don't want negative values in the transformed
> values?  Adding one to the raw counts is not sufficient. I should have said
> in my previous email, "the expected counts on the common scale".  If the
> size factor for a sample is 2, then an expected count of 1 leads to an
> expected count of 1/2 on the common scale (after accounting for size
> factors).
>
>
> On Sun, Apr 13, 2014 at 11:50 PM, Sophie Josephine Weiss <
> Sophie.Weiss@colorado.edu> wrote:
>
>> Hi Mike,
>> Thanks for your reply!  Ok, makes sense, but I added 1 to all my matrix
>> values, so the lowest value in the matrix is 1 - there are still negatives?
>> Thanks again,
>> Sophie
>>
>>
>> On Sun, Apr 13, 2014 at 9:01 PM, Michael Love <
>> michaelisaiahlove@gmail.com> wrote:
>>
>>> hi Sophie,
>>>
>>> The transformations in DESeq and DESeq2 are log2-like transformations.
>>> If the expected count is between 0 and 1, the values can be negative, this
>>> does not indicate a problem.
>>>
>>> Mike
>>>
>>>
>>> On Sun, Apr 13, 2014 at 5:17 PM, Sophie Josephine Weiss <
>>> Sophie.Weiss@colorado.edu> wrote:
>>>
>>>> Hello,
>>>> I have microbiome data with no replicates, from different conditions.
>>>>  I am
>>>> trying to transform the data using the DESeq method, as described in
>>>> McMurdie and Holmes 2014.
>>>>
>>>> The attached file is the definition I am using, as per the supplemental
>>>> info in McMurdie and Holmes 2014, and the .biom file I am using.
>>>>
>>>> Thank you for your help,
>>>> Sophie
>>>>
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>>>>
>>>
>>>
>>
>

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