I am currently working on a longitudinal multi-omics study involving two experimental groups: one with drug A intervention and another with drug A+B intervention, each consisting of 40 samples. We are collecting fecal and blood samples at baseline, 1 week, and 2 weeks for multi-omics analyses, including blood transcriptomics, targeted blood proteomics, targeted metabolomics in both blood and feces, and metagenomics.
I am interested in exploring whether TkNA can be applied to perform causal analysis in this context. Specifically, can TkNA handle such longitudinal data across different omics types? If so, do you have any recommendations or best practices for implementing TkNA in this study design?
Dear TkNA Team,
I am currently working on a longitudinal multi-omics study involving two experimental groups: one with drug A intervention and another with drug A+B intervention, each consisting of 40 samples. We are collecting fecal and blood samples at baseline, 1 week, and 2 weeks for multi-omics analyses, including blood transcriptomics, targeted blood proteomics, targeted metabolomics in both blood and feces, and metagenomics.
I am interested in exploring whether TkNA can be applied to perform causal analysis in this context. Specifically, can TkNA handle such longitudinal data across different omics types? If so, do you have any recommendations or best practices for implementing TkNA in this study design?
Thank you for your time and guidance.