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Metabolomics data processing for the ADNI data sets.

Project description

Metabo_ADNI

PyPI version

Metabolomics data processing for the ADNI data sets. Currently, only supports the Biocrates p180 and Nightingale NMR platforms.

Installation

metabo_adni is distributed as a python package, so install it by running:

pip install metabo_adni

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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