Efficient detection of decentralized biomarkers of groups of dna sequences in microbiome dna

A system for detecting biomarkers in microbiome DNA of one or more livestock hosts to predict a biological condition, the system comprising:

• one or more memories configured to store a plurality of microbiome DNA sequences, sequenced from microbiome DNA of one or more livestock hosts;
• and
• one or more processors configured to:
• generate a microbiome network comprising a plurality of nodes representing the respective plurality of microbiome DNA sequences and a plurality of edges representing a co-occurrence of each pair of microbiome DNA sequences in a same sample or sub-length of the microbiome DNA,
• bundle, into distinct groups, microbiome DNA sequences represented by nodes based on the node's degree, the degree of each node quantifying a number of edges that contain the node indicating a number of unique microbiome DNA sequences that co-occur with the microbiome DNA sequence represented by the node in the same sample or sub-length of the microbiome DNA,
• validate groups of microbiome DNA sequences that each have an internal connectivity between nodes of the same group that satisfies an anomaly condition indicating the microbiome DNA sequences of that group co-occur with a probability that is unlikely randomly statistical,
• generate a training dataset correlating the validated groups of microbiome DNA sequences from one or more livestock hosts with a biological condition measured in one or more livestock hosts, and
• train a machine learning model with the training dataset to input microbiome DNA sequences from one or more livestock hosts and predict the biological condition for one or more livestock hosts.