Metabolomics data processing for the ADNI data sets.
Project description
Metabo_ADNI
Metabolomics data processing for the ADNI data sets. Currently, only supports the Biocrates p180 and Nightingale NMR platforms.
Installation
- Clone the repo
git clone https://github.com/tomszar/adni_metabolomics.git
- Install metabo_adni
cd adni_metabolomics
pip install .
Usage
In the folder with the required datasets, simply run:
clean_files
And metabo_adni will run with the default parameters. Note: do not change the original name of the files.
Options
-D
: define the directory were the files are located. Default, current working directory-P
: define the platform, either p180 or nmr. Default, p180-F
: define the fasting file. Default, BIOMARK.csv-L
: define the directory were the LOD p180 files are located. Default, current working directory--mmc
: remove metabolites with missing proportions greater than cutoff. Default, 0.2--mpc
: remove participants with missing proportions greater than cutoff. Default, 0.2--cv
: remove metabolites with CV values greater than cutoff. Default, 0.2--icc
: remove metabolites with ICC values lower than cutoff. Default, 0.65--log2
: apply log2 transformation to metabolite concentration values--merge
: merge data frames across cohorts--zscore
: apply zscore transformation to metabolite concentration values--winsorize
: winsorize extreme values (more than 3 std of mean)--remove-moutliers
: remove multivariate outliers using the Mahalanobis distance--residualize-meds
: replace metabolite values with residuals from a regression with medication intake. Note that residuals are scaled to unit variance
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