YOLO Lab - Microbiome Research.

We perform multiple microbiome computational projects in collaborations with the Koren lab in Tzfat, and other labs. We develop diagnostic and prognostic tools based on a combination of microbiome and machine learning, as well as advanced methods to predict microbiome dynamics. These projects combine advanced machine learning with the complex dynamics of the microbiome.

Microbiome Preprocess

TEXT HERE

Visualization for microbiome analysis.

We developed several plots that may facilitate in understanding the complicated structure of the microbiome and its connections to different phenomena.

Plot/plot_relationship_between_features.py

After the projection of the microbiome to a lower dimension denoted by n, iterate through all n chose two sub groups of columns in the data, and plot the relationship between them.colored by a categorical column inserted.

For example:

Plot/plot_time_series_analysis.py

After the projection of the microbiome to a lower dimension, the following function aims to visualize the differences between two groups (b.g Normal vs Cancer) for each feature separately through time. T-test will be performed between all pairs of groups (component split by a specific timepoint->split by a binary attribute->perform ttest between the groups)

Plot/plot_relative_frequency.py

after the data has been preprocessed, and grouped into a taxonomical level, the following function shows the prevelence of each OTU in each person, and groups them all in a singular plot.