RNA‐Seq has emerged as a powerful method, applying transcriptome analysis to a wider range of organisms—most significantly, non‐model organisms lacking prior genomic sequencing. Whereas an initial concern of
RNA-Seq analysis to capture the transcriptome landscape of a single cell 热度: 转录组测序(RNA-seq)技术 热度: RNA-Seqmethodsfortranscriptomeanalysis RadmilaHrdlickova 1 ,MasoudToloue 1,* ,andBinTian 2,* 1 BiooScientificInc.,Austin,TX,USA ...
在科研领域,RNA-Seq 是分析基因表达和发现新种类RNA的常用方法;在精准医疗领域,靶向富集,特别是杂交捕获技术已经越来越多地应用于检测RNA水平上的融合突变,而基因融合可能会激活原癌基因、失活抑癌基因,从而驱动肿瘤的发生发展,同时也是很多癌症的微小病灶残留(MRD)靶点。 尽管现有技术方案允许对RNA 分子进行直接测序,...
we applied methods used for single cell RNA-Seq (scRNA-Seq) in previous studies16. In the scRNA-Seq method, the amount of input RNA was small, therefore all samples were pooled after being indexed by an index-added primer during the RT step. Furthermore, previous studies employed tagmentati...
RNA-Seq Methods for NGS Targeted Sequencing Approaches for NGS Data considerations for Human Genome Sequencing Introduction Ribonucleic acid (RNA) are polymeric molecules consisting of nucleotides, essential in the coding, decoding, regulation, and expressi...
Systematic assessment of long-read RNA-seq methods for transcript identification and quantification This Registered Report presents the results of the Long-read RNA-Seq Genome Annotation Assessment Project, which is a community effort for benchmarking long-read methods for transcriptome analyses, includin...
RNA-Seq Methods for NGS Targeted Sequencing Approaches for NGS Data considerations for Human Genome Sequencing Introduction Ribonucleic acid (RNA) are polymeric molecules consisting of nucleotides, essential in the coding, decoding, regulation, and expr...
空间RNA-seq(Spatially resolved RNA-seq methods) Bulk RNA-seq和scRNA-seq可以提供很多信息,但是却不能描绘空间水平上的转录状态,也无法揭示细胞状态和转录的联系。目前空间组学(spatialomics)的方法有两种:空间编码(spatial encoding)和原位转录组(in situ transcriptomics)。...
RNAseq简介 转录组是连接遗传信息与生物功能的桥梁,在广义上指在相同生理条件下的一个或一群细胞中所能转录出的所有RNA的总和,包括编码RNA及非编码RNA;狭义上指所有mRNA的集合[1]。转录组测序分析(RNA-seq)通过提取所要研究的mRNA,将其反转录成cDNA文库,在DNA小片段两端加上接头,利用高通量测序技术统计相关小片段...
HISAT全称为Hierarchical Indexing for Spliced Alignment of Transcripts,由约翰霍普金斯大学开发。它取代Bowtie/TopHat程序,能够将RNA-Seq的读取与基因组进行快速比对。这项成果发表在3月9日的《Nature Methods》上。 HISAT利用大量FM索引,以覆盖整个基因组。以人类基因组为例,它需要48,000个索引,每个索引代表~64,000...