omeClust: multi-resolution clustering of omics data
omeClust is a clustering method that detects clusters of features using omics data and scores metadata (resolution score) based on their influences in clustering. The similarity of features within each cluster can be different (different resolution). Resolution of similarity score takes to account not only similarity between measurements and also the structure in a hierarchical structure of data and number of features which group together.
Citation:
Ali Rahnavard, Suvo Chatterjee, Bahar Sayoldin, Keith A. Crandall, Fasil Tekola-Ayele, and Himel Mallick (2021). Omics community detection using multi-resolution clustering. Bioinformatics, 37(20):3588-3594, https://github.com/omicsEye/omeClust/.
Read more - Github omeClust