Back to Blog
Rna sequence7/20/2023 ![]() ![]() C., Sage, F., Vértesy, Á., Spanjaard, B., Peterson-Maduro, J., Baron, C. Microbiology and Molecular Biology Reviews: MMBR, 68, 538-559. Single-cell microbiology: Tools, technologies, and applications. Design and computational analysis of single-cell RNA-sequencing experiments. HTSeq-a Python framework to work with high-throughput sequencing data. RNA sequencing gene expression profiling single-cell analysis.Īnders, S., Pyl, P. Here, we present the most common scRNA-seq protocols in use today and the basics of data analysis and discuss factors that are important to consider before planning and designing an scRNA-seq project. By isolating single cells, capturing their transcripts, and generating sequencing libraries in which the transcripts are mapped to individual cells, scRNA-seq allows assessment of fundamental biological properties of cell populations and biological systems at unprecedented resolution. ![]() Single-cell RNA-seq (scRNA-seq) represents an approach to overcome this problem. However, RNA-seq is typically performed in "bulk," and the data represent an average of gene expression patterns across thousands to millions of cells this might obscure biologically relevant differences between cells. The opportunity to study entire transcriptomes in great detail using RNA sequencing (RNA-seq) has fueled many important discoveries and is now a routine method in biomedical research. During the last decade, high-throughput sequencing methods have revolutionized the entire field of biology. ![]()
0 Comments
Read More
Leave a Reply. |