Dynamics analysis for longitudinal community omics
Longitudinal community omics
—LCO—
In LCO, researchers study omics datasets belonging to different sources, times, body sites, or different hosts with the aim of unraveling spatial, temporal, or clinical patterns in the form and function of the microbiota.
Community multiomics datasets can be obtained from metagenomic, metatranscriptomic, metaproteomic or community metabolomic samples.
dynOmics is a software suite engineered to support the analysis of the dynamics of ranking processes in biological complex systems
In this framework, a dynamics analysis may unveil details of processes associated with different spatial or time scales, including intra-microbiome and host-microbiome interactions. Although dynOmics is oriented to LCO, it is general enough to be able to deal with ranking processes in any complex system or to include other biochemical datasets, such as consumption and growth data.
Dynomics is free software and will be soon available on GitHub.
For clinical, environmental, or industrial applications
dynOmics enables dynamic analysis of LCO samples of diverse origins (such as clinical, environmental, or industrial) and constituted in temporal, spatial, or any other kind of series.
dynOmics performs a battery of tests on the data such as Taylor's law fit, absolute and zero relative frequencies study, 2D-deviation check, multi-axis clustered correlation analysis, and rank dynamics and stability detailed evaluation.
dynOmics is parallelized to automatically analyze several LCO datasets concurrently and obtain global statistics and plots
We will provide more details in a forthcoming publication.