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 ([e-mail])
and Till Birkner  ([e-mail])

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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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MetaDrugs 工作流
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用于研究心血管代谢疾病中药物-宿主-微生物组关联的数据分析流程（基于MetaCardis队列）。

如有疑问或需求，请联系：
Sofia K. Forslund（[e-mail]）
以及 Till Birkner（[e-mail]）

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内容说明：
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数据文件：
metadata.tar.gz - 已归档的队列元数据文件*
input_features.tar.gz - 已归档的预处理血清、尿液代谢组与肠道微生物组特征文件
output_complete.tar.gz - 已归档的各输入特征文件对应的示例分析结果文件
output_rerun.tar.gz - 已归档的空目录，用于按照本文档说明生成测试结果文件

*请注意：由于与丹麦数据保护法存在冲突，本仓库中已移除该队列丹麦亚组的元数据。如需获取完整元数据，请提交逐案访问申请，我们将酌情评估。
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文本文件：
归档于feature_names.tar.gz中：
atcs_names - ATC（Anatomical Therapeutic Chemical）药物化合物的完整名称
contrast_names - 疾病比较组的完整名称
file_names - input_features文件夹内各文件的简要说明
gmm_names - GMM（Gaussian Mixture Model）模块的完整名称
kegg_names - KEGG（Kyoto Encyclopedia of Genes and Genomes）模块的完整名称
ko_names - KO（K Ortholog）模块的完整名称
metadata_names - 元数据特征的完整名称
mOTU_names - mOTU（metagenomic Operational Taxonomic Unit）名称
taxon_names - 宏基因组学数据的分类单元名称
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脚本文件：
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runFrame.r - 调用分析流程的主包装脚本
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runFrame_rel_comb.r - 用于计算药物联合效应的脚本
runFrame_rel.r - 用于计算药物剂量效应的脚本
testCombPresenceSeparate.r - 用于检验优于单一药物效应的显著药物联合效应
testDosagePresenceSeparate.pl - 用于检验优于单一药物效应的显著药物剂量效应
testDosagePresenceSeparateNegative.pl - 用于检验优于单一药物效应的独特药物剂量效应
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prettifyResults_uncollapsed.pl - 用于生成并格式化单份分析结果文件的包装脚本
makeTables.r - 用于生成包含分析结果的Excel表格的包装脚本
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示例结果文件：
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output_all_formatted_noc_uncollapsed_complete.tsv - 整合了所有疾病-药物-宿主-微生物组特征分析结果的单文件。
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