Clustering and classification software for sperm subpopulation analysis

BUCHELLY IMBACHÍ, FRANCISCO; ZALAZAR, LUCÍA; PASTORE, JUAN IGNACIO; NICOLLI, ANABELLA; LEDESMA, ALBA; HOZBOR, FEDERICO A.; CESARI, ANDREINA; BALLARIN, VIRGINIA

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

Taylor & Francis

Año: 2022 p. 1 - 14

2168-1163

In this paper, we present the Sperm Motility Tracker v2.0 that integrates a clustering module to the typical CASA sperm motility analysis adapted to semen from different species. The novelty of the new software is the integration of a friendly tool that allows researchers and clinical staff to identify sperm subpopulations by a simple procedure. Partitioning is performed by a hierarchical clustering based on selected motility parameters that can be selected automatically or manually. To show the performance of the proposed approach, we assayed a simple cryopreservation approach to compare sperm samples by using two different extenders.After clustering, we could identify three significant subpopulations according to the automaticallysuggested classifier parameters. This grouping was validated over fresh semen and was in accordance with the physiological status of the cell population. We validate the results over fresh semen, obtaining clusters according to the physiological status of the cell population. Subpopulation analysis highlights the results hidden by the standard population analysis.This new software version offers users a useful and friendly tool for sperm motility subpopulationanalysis in the veterinarian and biomedical fields.