Tumors: scRNA-seq has proven to be an invaluable tool in understanding the mechanisms behind tumor development. Its application in tumor analysis has shed light on previously overlooked or underappreciated cell populations. For instance, scRNA-seq studies of pancreatic ductal adenocarcinoma (PDA) highlighted the importance and heterogeneity of cancer-associated fibroblasts (CAFs). It was discove..

Cell-type Annotation: One of the major advantages of scRNA-seq is its ability to identify a wide variety of cell populations, including rare cell types. This technique can reveal previously unknown cell populations and provide essential insights into how specific cell groups are involved in disease environments or drug treatments. However, cell group identification is a highly labor-intensive pr..

Common RNA-seq Data Analysis Workflow: 1. Quality Control: Once sequencing data for the extracted RNA is received, the quality of the data is assessed using tools like FASTQC. Any adapters used during sequencing are removed using tools such as Trimmomatic. 2. Read Alignment: The quality-controlled reads are then mapped to a reference genome using alignment tools like STAR. While there are severa..