CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2023-12-18 DOI:10.1093/bioinformatics/btad759
Anisha Haldar, Vishal H Oza, Nathaniel S DeVoss, Amanda D Clark, Brittany N Lasseigne
{"title":"CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis","authors":"Anisha Haldar, Vishal H Oza, Nathaniel S DeVoss, Amanda D Clark, Brittany N Lasseigne","doi":"10.1093/bioinformatics/btad759","DOIUrl":null,"url":null,"abstract":"Summary High throughput sequencing technologies have enabled cross-species comparative transcriptomic studies; however, there are numerous challenges for these studies due to biological and technical factors. We developed CoSIA (Cross-Species Investigation and Analysis), an Bioconductor R package and Shiny app that provides an alternative framework for cross-species transcriptomic comparison of non-diseased wild-type RNA sequencing gene expression data from Bgee across tissues and species (human, mouse, rat, zebrafish, fly, and nematode) through visualization of variability, diversity, and specificity metrics. Availability and Implementation https://github.com/lasseignelab/CoSIA Supplementary information See Supplementary Material","PeriodicalId":8903,"journal":{"name":"Bioinformatics","volume":"43 1","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btad759","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Summary High throughput sequencing technologies have enabled cross-species comparative transcriptomic studies; however, there are numerous challenges for these studies due to biological and technical factors. We developed CoSIA (Cross-Species Investigation and Analysis), an Bioconductor R package and Shiny app that provides an alternative framework for cross-species transcriptomic comparison of non-diseased wild-type RNA sequencing gene expression data from Bgee across tissues and species (human, mouse, rat, zebrafish, fly, and nematode) through visualization of variability, diversity, and specificity metrics. Availability and Implementation https://github.com/lasseignelab/CoSIA Supplementary information See Supplementary Material
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
CoSIA:用于 CrOss 物种调查和分析的 R Bioconductor 软件包
摘要 高通量测序技术使跨物种比较转录组研究成为可能;然而,由于生物和技术因素,这些研究面临着诸多挑战。我们开发了 CoSIA(跨物种调查与分析),它是一个 Bioconductor R 软件包和 Shiny 应用程序,通过可视化的变异性、多样性和特异性指标,为来自 Bgee 的跨组织和物种(人、小鼠、大鼠、斑马鱼、苍蝇和线虫)非疾病野生型 RNA 测序基因表达数据的跨物种转录组比较提供了一个替代框架。可用性和实施 https://github.com/lasseignelab/CoSIA 补充信息 见补充材料
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
期刊介绍: The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
期刊最新文献
MEHunter: Transformer-based mobile element variant detection from long reads Metabolic syndrome may be more frequent in treatment-naive sarcoidosis patients. Coracle—A Machine Learning Framework to Identify Bacteria Associated with Continuous Variables CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1