I-SVVS : Integrative stochastic variational variable selection

Publication

Dang, Tung, et al. "I-SVVS: Integrative stochastic variational variable selection to explore joint patterns of multi-omics microbiome data" bioRxiv (2024): 2024-10 | https://doi.org/10.3389/fninf.2023.1266713

The workflow of the algorithm

Directory structure

Data

• The main files for dataset A of our paper in the data/ folder include:
  • datasetA_microbiome.csv: a microbiome OTU count table for dataset A
  • datasetA_metabolome.csv: a metabolome table for dataset A
  • datasetA_microbiome-tree.qza: microbiome phylogenetic tree for dataset A
• Please follow instructions in the haddad_osa github repo to get OTU tables, metabolome and microbiome phylogenetic tree for datasets B.
• Please follow instructions in the MicrobiomeHD github repo to get OTU tables, metabolome and microbiome phylogenetic tree for datasets C.

Source code

All of the code is in the src/ folder, you can use to re-make the analyses in the paper:

• Integrated_SVVS.py: file contains Python codes for I-SVVS algorithm that analyze microbiome and metabolome datasets.
• DMM_SVVS.py: file contains Python codes for analyzing only microbiome.
• GMM_SVVS.py: file contains Python codes for analyzing only metabolome.

If you have any problem, please contact me via email: [email protected]