MAMS:矩阵和分析元数据标准,促进单细胞数据的统一和可重复性

IF 10.1 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Genome Biology Pub Date : 2024-08-01 DOI:10.1186/s13059-024-03349-w
Irzam Sarfraz, Yichen Wang, Amulya Shastry, Wei Kheng Teh, Artem Sokolov, Brian R. Herb, Heather H. Creasy, Isaac Virshup, Ruben Dries, Kylee Degatano, Anup Mahurkar, Daniel J. Schnell, Pedro Madrigal, Jason Hilton, Nils Gehlenborg, Timothy Tickle, Joshua D. Campbell
{"title":"MAMS:矩阵和分析元数据标准,促进单细胞数据的统一和可重复性","authors":"Irzam Sarfraz, Yichen Wang, Amulya Shastry, Wei Kheng Teh, Artem Sokolov, Brian R. Herb, Heather H. Creasy, Isaac Virshup, Ruben Dries, Kylee Degatano, Anup Mahurkar, Daniel J. Schnell, Pedro Madrigal, Jason Hilton, Nils Gehlenborg, Timothy Tickle, Joshua D. Campbell","doi":"10.1186/s13059-024-03349-w","DOIUrl":null,"url":null,"abstract":"Many datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While biospecimen and experimental information is often captured, detailed metadata standards related to data matrices and analysis workflows are currently lacking. To address this, we develop the matrix and analysis metadata standards (MAMS) to serve as a resource for data centers, repositories, and tool developers. We define metadata fields for matrices and parameters commonly utilized in analytical workflows and developed the rmams package to extract MAMS from single-cell objects. Overall, MAMS promotes the harmonization, integration, and reproducibility of single-cell data across platforms.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":10.1000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MAMS: matrix and analysis metadata standards to facilitate harmonization and reproducibility of single-cell data\",\"authors\":\"Irzam Sarfraz, Yichen Wang, Amulya Shastry, Wei Kheng Teh, Artem Sokolov, Brian R. Herb, Heather H. Creasy, Isaac Virshup, Ruben Dries, Kylee Degatano, Anup Mahurkar, Daniel J. Schnell, Pedro Madrigal, Jason Hilton, Nils Gehlenborg, Timothy Tickle, Joshua D. Campbell\",\"doi\":\"10.1186/s13059-024-03349-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While biospecimen and experimental information is often captured, detailed metadata standards related to data matrices and analysis workflows are currently lacking. To address this, we develop the matrix and analysis metadata standards (MAMS) to serve as a resource for data centers, repositories, and tool developers. We define metadata fields for matrices and parameters commonly utilized in analytical workflows and developed the rmams package to extract MAMS from single-cell objects. Overall, MAMS promotes the harmonization, integration, and reproducibility of single-cell data across platforms.\",\"PeriodicalId\":12611,\"journal\":{\"name\":\"Genome Biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":10.1000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13059-024-03349-w\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13059-024-03349-w","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

许多数据集是由试图以单细胞分辨率描述健康和疾病组织特征的联盟制作的。虽然生物样本和实验信息经常被采集,但目前还缺乏与数据矩阵和分析工作流程相关的详细元数据标准。为了解决这个问题,我们开发了矩阵和分析元数据标准(MAMS),作为数据中心、资料库和工具开发人员的资源。我们为分析工作流程中常用的矩阵和参数定义了元数据字段,并开发了 rmams 软件包,用于从单细胞对象中提取 MAMS。总之,MAMS 促进了跨平台单细胞数据的协调、整合和可重现性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
MAMS: matrix and analysis metadata standards to facilitate harmonization and reproducibility of single-cell data
Many datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While biospecimen and experimental information is often captured, detailed metadata standards related to data matrices and analysis workflows are currently lacking. To address this, we develop the matrix and analysis metadata standards (MAMS) to serve as a resource for data centers, repositories, and tool developers. We define metadata fields for matrices and parameters commonly utilized in analytical workflows and developed the rmams package to extract MAMS from single-cell objects. Overall, MAMS promotes the harmonization, integration, and reproducibility of single-cell data across platforms.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Genome Biology
Genome Biology Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
21.00
自引率
3.30%
发文量
241
审稿时长
2 months
期刊介绍: Genome Biology stands as a premier platform for exceptional research across all domains of biology and biomedicine, explored through a genomic and post-genomic lens. With an impressive impact factor of 12.3 (2022),* the journal secures its position as the 3rd-ranked research journal in the Genetics and Heredity category and the 2nd-ranked research journal in the Biotechnology and Applied Microbiology category by Thomson Reuters. Notably, Genome Biology holds the distinction of being the highest-ranked open-access journal in this category. Our dedicated team of highly trained in-house Editors collaborates closely with our esteemed Editorial Board of international experts, ensuring the journal remains on the forefront of scientific advances and community standards. Regular engagement with researchers at conferences and institute visits underscores our commitment to staying abreast of the latest developments in the field.
期刊最新文献
Atlas of telomeric repeat diversity in Arabidopsis thaliana ESCHR: a hyperparameter-randomized ensemble approach for robust clustering across diverse datasets Splam: a deep-learning-based splice site predictor that improves spliced alignments Dimension reduction, cell clustering, and cell–cell communication inference for single-cell transcriptomics with DcjComm A comprehensive map of the aging blood methylome in humans
×
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