Before I get into CLR transformation, is there any step to change my OTU table ?

General Discussion
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Hello ! Folks.

I'm trying integrate OTU table data from different batches.

Hence, I'm considering to do normalization before any further analysis.

I have looked through normalization methods and found that Centered Log ratio was one of the most mentioned method.
(I know it is built in many plug in of qiime. But I have to do other analysis in addition to the functions in qiime2)

However, I found that a sentence saying "Make Pseudocount before CLR"). Is there any pre-step before do CLR transformation ? Or the pseudocount would be made in the normal process integrated in CLR transformation ? I will use R, ALDEx2 package / or Python sckit-bio package to do my table transformation to CLR form.

Please suggest me and explain me about the question.

Many thanks for your help.

2

Hello!
To get CLR data like in aldex2, I used this code:

import pandas as pd
from skbio.stats.composition import clr


# Function from absolute abundances to clr
def to_clr(data):
    data += 1                                  # add pseudocount
    data = data.div(data.sum(axis=0), axis=1)  # relative abund
    return pd.DataFrame(clr(data.T), columns=data.index, index=data.columns).T #clr

As well as I remember I got identical results as in aldex2.
So, I added pseudocounts, converted to relative abundances and applied CLR from skbio. It was also neccessary to transpose the data before clr and then transpose it back.

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Thank you tomanix !! This would be a definitely big help for me ^^ I'll try this and match the result from R.

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Dear timanix, I have one more question to it. When I try the from skbio.stats.composition import clr commend, 'No module named 'skbio' appears even after I installed 'scikit-bio' package using 'conda install scikit-bio' commend.

How did you prepare the using of librarie ?

Thank you for your kindness.

5

Hi!
I just run the code inside of qiime2 env since I am a little bit lazy and most of the required libraries already installed there.

6

Thank you. I've try to install the 'scikit-bio' package in the Windows environment, and that was the problem.

Now I successfully did the analysis using the package in the linux environment. (scikit-bio package could be installed only under linux)

Thank you !!

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7

does your function assumes taxa as columns ans samples as index or vice versa?

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It takes a table as in feature table, so features as index and samples as columns.

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Thanks, wan't so sure because of the pandas transposed representation (Feature table importing) while saving a df based on feature table (df.feature_table.view(pd.DataFrame))

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