Generalized nestedness detection in microbial communities

A computer-implemented method for analyzing nestedness in a microbial community comprising:

• generating an input matrix with 1s and 0s for one or more samples from the microbial community, wherein 1 represents the presence of a microbe in the one or more samples and 0 represents the absence of microbes in the one or more samples;
• computing a filtration matrix for the one or more samples;
• computing a C̆ech complex persistent homology for the filtration matrix in at least two dimensions;
• and
• displaying the persistent homology of the filtration matrix with at least one persistent homology barcode, wherein the at least one persistent homology barcode has a shape and length that provides information on the nestedness of the microbes in the microbial community.

A computer-implemented method for analyzing nestedness in a microbial community comprising:

• generating an input matrix with 1s and 0s for one or more samples from the microbial community, wherein 1 represents the presence of a microbe in the one or more samples and 0 represents the absence of microbes in the one or more samples;
• computing a Jaccard similarity filtration matrix for the one or more samples;
• computing a C̆ech complex persistent homology for the filtration matrix in at least two dimensions;
• and
• displaying the persistent homology of the filtration matrix with at least one persistent homology barcode, wherein the at least one persistent homology barcode has a shape and length that provides information on the nestedness of the microbes in the microbial community.

A computer-implemented method for analyzing nestedness in a microbial community comprising:

• generating an input matrix with 1s and 0s for one or more samples from the microbial community, wherein 1 represents the presence of a microbe in the one or more samples and 0 represents the absence of microbes in the one or more samples;
• computing a filtration matrix with a min(com1/sum(1)) computation for the one or more samples;
• computing a C̆ech complex persistent homology for the filtration matrix in at least two dimensions;
• and
• displaying the persistent homology of the filtration matrix with at least one persistent homology barcode, wherein the at least one persistent homology barcode has a shape and length that provides information on the nestedness of the microbes in the microbial community.

A computer program product for analyzing nestedness in a microbial community comprising:

• program instructions on one or more computer readable storage media for generating an input matrix with 1s and 0s for one or more samples from the microbial community, wherein 1 represents the presence of a microbe in the one or more samples and 0 represents the absence of microbes in the one or more samples;
• program instructions on one or more computer readable storage media for computing a filtration matrix for the one or more samples;
• program instructions on one or more computer readable storage media for computing persistent homology for the filtration matrix in at least two dimensions;
• and
• program instructions on one or more computer readable storage media for displaying the persistent homology of the filtration matrix with at least one persistent homology barcode, wherein the at least one persistent homology barcode has a shape and length that provides information on the nestedness of the microbes in the microbial community.