Data analysis pipeline for investigating drug-host-microbiome relationships in cardiometabolic disease (MetaCardis cohort).

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MetaDrugs workflow
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Data analysis pipeline for investigating drug-host-microbiome relationships in cardiometabolic disease (MetaCardis cohort).

For questions and requests, please contact:
Sofia K. Forslund (sofia.forslund@mdc-berlin.de)
and Till Birkner  (till.birkner@mdc-berlin.de)

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Contents:
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Data files:
metadata.tar.gz - archived cohort metadata files*
input_features.tar.gz - archived preprocessed serum and urine metabolome and gut microbiome features
output_complete.tar.gz - archived example analysis output files for each of the input feature file
output_rerun.tar.gz - archived empty directory for generating test output files as described in this document

*Please note: Due to conflicts with Danish Data Protection laws, metadata from the Danish subset of the cohort were removed in this repository. Please reach out for a potential case-by-case access request for access to the complete set of metadata.
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Text files:
archived in feature_names.tar.gz:
atcs_names - full names for atcs drug compounds
contrast_names - full names for disease comparison groups
file_names - brief description of the files in input_features folder
gmm_names - full names of GMM modules
kegg_names - full names of KEGG modules
ko_names - full names of KO modules
metadata_names - full names of metadata features
mOTU_names - species names for metagenomics data
taxon_names - taxon names for metagenomics data
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Scripts:
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runFrame.r - main wrapper script envoking the analysis pipeline
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runFrame_rel_comb.r - script calculating drug combination effects
runFrame_rel.r - script calculating dosage effects
testCombPresenceSeparate.r - testing of significant drug combination effects beyond single drug effects
testDosagePresenceSeparate.pl - testing of significant drug dosage effects beyond single drug effects
testDosagePresenceSeparateNegative.pl - testing of unique drug dosage effects beyond single drug effects
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prettifyResults_uncollapsed.pl - wrapper scripts to create and format a single analysis output file
makeTables.r - wrapper script to make excel tables with analysis results
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Example output file:
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output_all_formatted_noc_uncollapsed_complete.tsv - contains all disease-drug-host-microbiome feature analysis results in one place.
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