Selecting representative samples from complex biological datasets using k-medoids clustering

Autor:	Li, Lei, Wilson, Patrick C.
Rok vydání:	2022
Předmět:	Single-cell Sampling k-medoids R Antibody candidate selection
DOI:	10.5281/zenodo.6639035
Popis:	This method quantifies the relationships/similarities among samples using their Euclidian distances by vectorizing all given properties, and then determines an appropriate sample size by evaluating the coverage of key proprieties from multiple candidate sizes, following by a k-medoids clustering to group samples into several clusters, and selects centers from each cluster as the most representatives.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a43bac0d4b23e1ded2661929739beaa9 Zobrazit plný text záznamu