Abstract

In vivo derived oocytes are held as the gold standard for viability, other known origination methods are sub-par by comparison. Due to the low-viability of oocytes originating from these alternate methods, research was conducted to determine and quantify the validity of these alternate origination methods. However, the larger question of viability is on the individual oocyte level. We propose and compare methods of measurement based on gene expression profiles (GEPs) in order to assess oocyte viability, independent of oocyte origin. The first is based on a previously published wRMSD quantification of GEP differences. We also consider three novel methods: a distance comparison method, a tolerance interval method, and a classification-tree decision method; each utilizes a variable selection technique that focuses on the most differentially expressed genes. In our project, we obtain GEPs of individual swine oocytes and a general GEP distribution for in vivo oocytes. This distribution was the comparison standard for all oocytes, to gain a classification of viability. Each method is a valid method for driving viability decisions of the individual oocytes.

Keywords

Oocyte, Viability, Classification

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Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

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Jan 1st, 12:00 AM

Statistical Methods for Assessing Individual Oocyte Viability Through Gene Expression Profiles

In vivo derived oocytes are held as the gold standard for viability, other known origination methods are sub-par by comparison. Due to the low-viability of oocytes originating from these alternate methods, research was conducted to determine and quantify the validity of these alternate origination methods. However, the larger question of viability is on the individual oocyte level. We propose and compare methods of measurement based on gene expression profiles (GEPs) in order to assess oocyte viability, independent of oocyte origin. The first is based on a previously published wRMSD quantification of GEP differences. We also consider three novel methods: a distance comparison method, a tolerance interval method, and a classification-tree decision method; each utilizes a variable selection technique that focuses on the most differentially expressed genes. In our project, we obtain GEPs of individual swine oocytes and a general GEP distribution for in vivo oocytes. This distribution was the comparison standard for all oocytes, to gain a classification of viability. Each method is a valid method for driving viability decisions of the individual oocytes.