TY - JOUR
T1 - NFnetFu
T2 - A novel workflow for microbiome data fusion
AU - Bisht, Vartika
AU - Acharjee, Animesh
AU - Gkoutos, Georgios V
PY - 2021/8
Y1 - 2021/8
N2 - Microbiome data analysis and its interpretation into meaningful biological insights remain very challenging for numerous reasons, perhaps most prominently, due to the need to account for multiple factors, including collinearity, sparsity (excessive zeros) and effect size, that the complex experimental workflow and subsequent downstream data analysis require. Moreover, a meaningful microbiome data analysis necessitates the development of interpretable models that incorporate inferences across available data as well as background biomedical knowledge. We developed a multimodal framework that considers sparsity (excessive zeros), lower effect size, intrinsically microbial correlations, i.e., collinearity, as well as background biomedical knowledge in the form of a cluster-infused enriched network architecture. Finally, our framework also provides a candidate taxa/Operational Taxonomic Unit (OTU) that can be targeted for future validation experiments. We have developed a tool, the term NFnetFU (Neuro Fuzzy network Fusion), that encompasses our framework and have made it freely available at https://github.com/VartikaBisht6197/NFnetFu.
AB - Microbiome data analysis and its interpretation into meaningful biological insights remain very challenging for numerous reasons, perhaps most prominently, due to the need to account for multiple factors, including collinearity, sparsity (excessive zeros) and effect size, that the complex experimental workflow and subsequent downstream data analysis require. Moreover, a meaningful microbiome data analysis necessitates the development of interpretable models that incorporate inferences across available data as well as background biomedical knowledge. We developed a multimodal framework that considers sparsity (excessive zeros), lower effect size, intrinsically microbial correlations, i.e., collinearity, as well as background biomedical knowledge in the form of a cluster-infused enriched network architecture. Finally, our framework also provides a candidate taxa/Operational Taxonomic Unit (OTU) that can be targeted for future validation experiments. We have developed a tool, the term NFnetFU (Neuro Fuzzy network Fusion), that encompasses our framework and have made it freely available at https://github.com/VartikaBisht6197/NFnetFu.
KW - Clustering
KW - Fuzzy inference
KW - Microbiome
KW - Network fusion
UR - http://www.scopus.com/inward/record.url?scp=85109200353&partnerID=8YFLogxK
U2 - 10.1016/j.compbiomed.2021.104556
DO - 10.1016/j.compbiomed.2021.104556
M3 - Article
C2 - 34216888
SN - 0010-4825
VL - 135
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
M1 - 104556
ER -