{"title":"Comparative De Novo Transcriptome Assembly of <i>Notophthalmus viridescens</i> RNA-seq Data using Two Commercial Software Programs.","authors":"Jonathan Chacon, Math P Cuajungco","doi":"10.32398/cjhp_20181601","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and purpose: </strong>The reduction of cost and ease of using core laboratories or commercial sequencing companies have allowed biomedical and health researchers alike to employ reference-based genomic or transcriptomic sequencing (RNA-seq) projects to expand their work. Non-reference based data analysis, in cases of inexperienced researchers, become more challenging despite the availability of many open source and commercial software programs.</p><p><strong>Methods: </strong>We performed de novo assembly of RNA-seq data obtained from a non-model organism (Eastern Newt skin) to compare data output of two commercially available software workflows.</p><p><strong>Results: </strong>Our results show that the software packages performed satisfactorily albeit with differences in how the annotated and novel transcripts were identified and listed.</p><p><strong>Conclusion: </strong>Overall, we conclude that the use of commercial software platforms has a clear advantage to that of open source programs because of convenience with data analysis workflows. One caveat is that users need to know the software's basic algorithm and technical approach, in order to determine the precision and validity of the data output. Thus, it is imperative that researchers fully evaluate the software according to their needs to determine their suitability.</p>","PeriodicalId":87431,"journal":{"name":"Californian journal of health promotion","volume":"16 1","pages":"46-53"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6205749/pdf/nihms-993830.pdf","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Californian journal of health promotion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32398/cjhp_20181601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Background and purpose: The reduction of cost and ease of using core laboratories or commercial sequencing companies have allowed biomedical and health researchers alike to employ reference-based genomic or transcriptomic sequencing (RNA-seq) projects to expand their work. Non-reference based data analysis, in cases of inexperienced researchers, become more challenging despite the availability of many open source and commercial software programs.
Methods: We performed de novo assembly of RNA-seq data obtained from a non-model organism (Eastern Newt skin) to compare data output of two commercially available software workflows.
Results: Our results show that the software packages performed satisfactorily albeit with differences in how the annotated and novel transcripts were identified and listed.
Conclusion: Overall, we conclude that the use of commercial software platforms has a clear advantage to that of open source programs because of convenience with data analysis workflows. One caveat is that users need to know the software's basic algorithm and technical approach, in order to determine the precision and validity of the data output. Thus, it is imperative that researchers fully evaluate the software according to their needs to determine their suitability.