基于以上问题,作者综述了目前scRNA-seq分析流程、步骤和方法(Figure 1),提出了一套目前最佳的实践分析流程,详见theislab/single-cell-tutorial. 这套分析流程在Jupyter–Ipython notebook进行,包括R和python语言,可推荐作为一套分析模版。 Figure 1. Schematic of a typical single-cell RNA-seq analysis workflow. ...
Single-cell RNA sequencing (scRNA-seq) is a popular and powerful technology that allows you to profile the whole transcriptome of a large number of individual cells. However, the analysis of the large volumes of data generated from these experiments requires specialized statistical and computational ...
Single cell sequencinguses optimized next-generation sequencing (NGS) technology to check the sequence information of a single cell. There is a higher resolution of cell differences and a better understanding of the functions of individual cells in the microenvironment. Sequencing the RNA expressed by...
Single-cell transcriptomics can profile thousands of cells in a single experiment and identify novel cell types, states and dynamics in a wide variety of tissues and organisms. Standard experimental protocols and analysis workflows have been developed to create single-cell transcriptomic maps from ...
Frequently asked questions around next-generation sequencing and single-cell RNA-seq sample preparation and order processing.
With emergence of single-cell biology and adaptation of various sequencing-based omics technologies, the study of chromatin accessibility at single cell resolution became possible owing to the development of single-cell ATAC sequencing (scATAC-seq). However, computational analysis of scATAC-seq data ...
single-cell RNA sequencing villus formation inflammatory bowel disease human fetal gut development intestinal stem cells pediatric Crohn's disease intestinal organoids Introduction Development of the human intestine is a highly complex process that requires synergy between a wide range of cell types. Subtl...
cell-level downstream analysis -细胞水平的下游分析 gene-level downstream analysis -基因水平的下游分析 1. Pre-processing and visualization experimental workflow single-cell dissociation, single-cell isolation, library construction, and sequencing 分别为以上四步走 ...
cellranger aggraggregates outputs from multiple runs ofcellranger countorcellranger multi, normalizing those runs to the same sequencing depth and then recomputing the feature-barcode matrices and analysis on the combined data. Theaggrpipeline can be used to combine data from multiple samples int...
Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack...