Journal
THERIOGENOLOGY
Volume 75, Issue 5, Pages 783-795Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.theriogenology.2010.11.034
Keywords
CASA; Automated semen analysis; Sperm subpopulations; Multivariate analysis; Cluster analysis
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Funding
- Ministry of Science and Innovation, Spain
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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. (C) 2011 Elsevier Inc. All rights reserved.
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