Eric M. Small , Daniel P. Felker , Olivia C. Heath , Ryla J. Cantergiani , Christine E. Robbins , Mary Ann Osley , Mark A. McCormick
{"title":"SPOCK, an R based package for high-throughput analysis of growth rate, survival, and chronological lifespan in yeast","authors":"Eric M. Small , Daniel P. Felker , Olivia C. Heath , Ryla J. Cantergiani , Christine E. Robbins , Mary Ann Osley , Mark A. McCormick","doi":"10.1016/j.tma.2020.08.003","DOIUrl":null,"url":null,"abstract":"<div><p>Plate-reader based methods for high-throughput measurement of growth rate, cellular survival, and chronological lifespan are a compelling addition to the already powerful toolbox of budding yeast <em>Saccharomyces cerevisiae</em> genetics. These methods have overcome many of the limits of traditional yeast biology techniques, but also present a new bottleneck at the point of data-analysis. Herein, we describe SPOCK (Survival Percentage and Outgrowth Collection Kit), an R-based package for the analysis of data created by high-throughput plate reader based methods. This package allows for the determination of chronological lifespan, cellular growth rate, and survival in an efficient, robust, and reproducible fashion.</p></div>","PeriodicalId":36555,"journal":{"name":"Translational Medicine of Aging","volume":"4 ","pages":"Pages 141-148"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.tma.2020.08.003","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational Medicine of Aging","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468501120300201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 8
Abstract
Plate-reader based methods for high-throughput measurement of growth rate, cellular survival, and chronological lifespan are a compelling addition to the already powerful toolbox of budding yeast Saccharomyces cerevisiae genetics. These methods have overcome many of the limits of traditional yeast biology techniques, but also present a new bottleneck at the point of data-analysis. Herein, we describe SPOCK (Survival Percentage and Outgrowth Collection Kit), an R-based package for the analysis of data created by high-throughput plate reader based methods. This package allows for the determination of chronological lifespan, cellular growth rate, and survival in an efficient, robust, and reproducible fashion.