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Statistical Series: Opportunities and challenges of sperm motility subpopulation analysis |
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| Authors: | Martínez-Pastor Felipe Tizado E Jorge Garde J Julian Anel Luis de Paz Paulino |
| Institution: | a INDEGSAL, University of León, 24071 León, Spain b Molecular Biology (Cell Biology), University of León, 24071, León, Spain c Zoology, Biodiversity and Environmental Management, University of León, 24071 León, Spain d Biology of Reproduction Group, National Wildlife Research Institute (IREC), CSIC-UCLM-JCCM, and Institute for Regional Development (IDR), 02071, Albacete, Spain, 02071, Albacete, Spain e Animal Reproduction and Obstetrics, University of León, 24071, León, Spain |
| Abstract: | Computer-assisted sperm analysis (CASA) allows assessing the motility of individual spermatozoa, generating huge datasets. These datasets can be analyzed using data mining techniques such as cluster analysis, to group the spermatozoa in subpopulations with biological meaning. This review considers the use of statistical techniques for clustering CASA data, their challenges and possibilities. There are many clustering approaches potentially useful for grouping sperm motility data, but some options may be more appropriate than others. Future development should focus not only in improvements of subpopulation analysis, but also in finding consistent biological meanings for these subpopulations. |
| Keywords: | CASA Automated semen analysis Sperm subpopulations Multivariate analysis Cluster analysis |
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