.png){kind=icon}
返回
Stable gene expression for normalisation and single-sample scoring
.png){kind=icon}
OA
AI
DOI：10.1093/nar/gkaa802.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Gene expression signatures have been critical in defining the molecular phenotypes of cells, tissues, and patient samples. Their most notable and widespread clinical application is stratification of breast cancer patients into molecular (PAM50) subtypes. The cost and relatively large amounts of fresh starting material required for whole-transcriptome sequencing has limited clinical application of thousands of existing gene signatures captured in repositories such as the Molecular Signature Database. We identified genes with stable expression across a range of abundances, and with a preserved relative ordering across thousands of samples, allowing signature scoring and supporting general data normalisation for transcriptomic data. Our new method, stingscore, quantifies and summarises relative expression levels of signature genes from individual samples through the inclusion of these 'stably-expressed genes'. We show that our list of stable genes has better stability across cancer and normal tissue data than previously proposed gene sets. Additionally, we show that signature scores computed from targeted transcript measurements using stingscore can predict docetaxel response in breast cancer patients. This new approach to gene expression signature analysis will facilitate the development of panel-type tests for gene expression signatures, thus supporting clinical translation of the powerful insights gained from cancer transcriptomic studies.
Keyword:
DECONVOLUTION
RECURRENCE
ASSAY
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
13.1
论文数:
3.6W
被引数:
29.0W
机构
引用论文
Peptaibolin: synthesis, 3D-structure, and membrane modifying properties of the natural antibiotic and selected analogues.png)
Tetrahedron
TetrahedronIF0
PREAI
分享收藏A new normalization for Nanostring nCounter gene expression dataNanostring nCounter基因表达数据的一种新的归一化方法NUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏Measurement of the multi-TeV neutrino interaction cross-section with IceCube using Earth absorptionNature
OAAI
NatureIF0
OAAI分享收藏A scaling normalization method for differential expression analysis of RNA-seq dataRna-seq数据差异表达分析的尺度归一化方法GENOME BIOLOGYOAAI
GENOME BIOLOGYIF9.4
OAAI分享收藏voom: precision weights unlock linear model analysis tools for RNA-seq read countsvoom: 精确权重解锁rna-seq读取计数的线性模型分析工具GENOME BIOLOGYOAAI
GENOME BIOLOGYIF9.4
OAAI分享收藏
查看更多内容