METAFlux可以根据bulk RNA-seq和scRNA-seq数据预测癌症代谢通量,以解决这些分析空白。METAFlux能够以nutrient-aware的方式使用癌症基因表达数据来表征整个代谢回路并输出non-degenerative通量。对于scRNA-seq 数据,METAFlux还检查TME中细胞类型之间的代谢异质性和相互作用。 METAFlux工作流程 METAFlux的性能测试 开发团队利用细胞...
1、ssGSEA 单样本基因集富集分析(single sample gene set enrichment analysis, ssGSEA),原理上与GSEA类似,不同的是GSEA 主要用于检测不同实验组(如实验组和对照组)之间基因集富集差异,而ssGSEA将样本内基因表达谱进行归一化处理,然后计算每个基因集对应的ssGSEA得分。通过这种方式,ssGSEA将单个样本的基因表达谱转换...
Bulk RNA数据基于细胞群体水平获得组织的平均特性,反映细胞群体的平均差异,而Single-cell RNA通过单个细胞的mRNA进行转录组分析,识别不同细胞亚群的细胞类型、状态和谱系,绘制细胞图谱、鉴定细胞异质性,可以精准解析细胞亚类功能及对疾病的影响[...
单细胞数据虽然提高了信息挖掘的颗粒度,但是经常比较遗憾的是没有一些的临床信息(如治疗响应、耐药、复发信息等),因此scRNA-seq与bulk RNA-seq联合分析应运而生,既满足临床问题的研究可行性又对齐了颗粒度。 说到scRNA-seq与bulk RNA-seq数据的联合分析,就不得不提及到Scissor这个利器了,该软件于2021年发表在神...
第六步,Using the integrated data, the single cells were classified according to their bulk RNA-seq counterparts, using the LogisticRegression function, specifying the liblinear solver, from the sklearn module in R via Reticulate.依据bulk的数据对单细胞进行数据划分(也就是定义),这里涉及到一些算法,py...
Single-cell RNA sequencing (scRNAseq) provides unprecedented resolution by analyzing individual infected cells, revealing remarkable cellular heterogeneity within the host response. A particularly innovative advancement, virus-inclusive single-cell RNA sequencing (viscRNA-seq), addresse...
single-cell sequencingimmune cellsPyrocytosis is involved in the development of abdominal aortic aneurysm (AAA), we explored the pyrocytosis-related hub genes in AAA and conducted a diagnostic model based on the pyrocytosis-related genes score (PRGs). A total of 2 bulk RNA-seq (GSE57691 and ...
Despite numerous TIME-related studies that have been carried out in bulk RNA-seq data, limited resolution and lack of cellular heterogeneity remain hindrances and obstacles to further exploration of TIME. Recently, single-cell RNA-seq (scRNA-seq) technology has flourished as a powerful platform for...
Integration of bulk RNA-seq and single-cell RNA-seq constructs: a cancer-associated fibroblasts-related signature to predict prognosis and therapeutic response in clear cell renal cell carcinoma. American Journal of Translational ResearchJiating CuiXuanzhen ZhouShuben Sun...
通过这样的反卷积过程,BisqueRNA能够基于批量RNA-seq数据估计出细胞类型的比例,从而提供了对样本中细胞异质性的洞察。这种方法在细胞组成分析中具有广泛的应用,并为我们理解组织和疾病发展提供了重要的信息。 总的来说这类bulk反卷积方法往往需要一个定义好细胞亚型类型的单细胞基因表达谱数据或者定义好细胞亚型的markers...