Classification of Mouse Sperm Motility Patterns Using an Automated Multiclass Support Vector Machines Model
Classification of Mouse Sperm Motility Patterns Using an Automated Multiclass Support Vector Machines Model
复制标题
DOI：
10.1095/biolreprod.110.088989
复制
发表时间：
2011-06-01
影响因子：
3.6
通讯作者：
O'Brien, Deborah A.
中科院分区：
文献类型：
--
作者：
Goodson, Summer G.;Zhang, Zhaojun;O'Brien, Deborah A.
活跃的精子运动，包括发生在雌性生殖道的从进行性运动到过度激活运动的转变，是哺乳动物正常受精所必需的。我们开发了一种自动化的定量方法，使用支持向量机（SVM）客观地对小鼠精子的五种不同的运动模式进行分类，支持向量机是监督机器学习中的一种常用方法。这个多类SVM模型是基于计算机辅助精子分析（CASA）在体外获能过程中捕获的2000多个精子轨迹，并在视觉上分为渐进、中等、过度激活、缓慢或弱运动。将与分类轨迹相关的参数纳入已建立的支持向量机算法，生成一系列方程。这些方程被整合到一个二叉决策树中，该决策树依次将未表征的轨道分类为不同的类别。第一个方程将CASA轨道分为有力和非有力两类。附加的方程将有力的轨道分类为渐进的、中间的或过度激活的轨道，将非有力的轨道分类为缓慢的或弱运动的轨道。我们的CASAnova软件使用这些支持向量机方程来自动分类单个精子的运动模式。比较有碳酸氢盐和没有碳酸氢盐孵育的精子的运动特征，证实了该模型区分体外获能过程中产生的过度激活的运动模式的能力。该模型准确地从具有严重运动缺陷的突变小鼠模型中分类精子的运动概况。将该模型应用于多个自交系的精子，揭示了精子运动谱的菌株依赖性差异。CASAnova提供了一个快速、可重复的平台，用于定量比较大型、异质小鼠精子的活力。
Vigorous sperm motility, including the transition from progressive to hyperactivated motility that occurs in the female reproductive tract, is required for normal fertilization in mammals. We developed an automated, quantitative method that objectively classifies five distinct motility patterns of mouse sperm using Support Vector Machines (SVM), a common method in supervised machine learning. This multiclass SVM model is based on more than 2000 sperm tracks that were captured by computer-assisted sperm analysis (CASA) during in vitro capacitation and visually classified as progressive, intermediate, hyperactivated, slow, or weakly motile. Parameters associated with the classified tracks were incorporated into established SVM algorithms to generate a series of equations. These equations were integrated into a binary decision tree that sequentially sorts uncharacterized tracks into distinct categories. The first equation sorts CASA tracks into vigorous and nonvigorous categories. Additional equations classify vigorous tracks as progressive, intermediate, or hyperactivated and nonvigorous tracks as slow or weakly motile. Our CASAnova software uses these SVM equations to classify individual sperm motility patterns automatically. Comparisons of motility profiles from sperm incubated with and without bicarbonate confirmed the ability of the model to distinguish hyperactivated patterns of motility that develop during in vitro capacitation. The model accurately classifies motility profiles of sperm from a mutant mouse model with severe motility defects. Application of the model to sperm from multiple inbred strains reveals strain-dependent differences in sperm motility profiles. CASAnova provides a rapid and reproducible platform for quantitative comparisons of motility in large, heterogeneous populations of mouse sperm.