Next-generation sequencing techniques has seen an unimaginable growth in the past two decades. The scope has really broadened, and it is now possible to look at a genome both at macro and micro levels. Single-Cell RNA sequencing (scRNA-seq) is one such technique which deals with understanding the transcriptome at a cellular level. Single cell RNA sequencing can provide unparalleled insights into the various cellular events. scRNA-seq has an advantage over the bulk RNA-seq studies since it provides higher resolution in terms of cell subsets diversity and individual cell heterogeneity in the organisms.

Single-cell genomic analysis has emerged as a powerful method for studying complex disease. By providing comprehensive analyses of individual cells, single-cell sequencing allows researchers to examine cellular heterogeneity, which especially useful in oncology, neurology, immunology, and developmental research.

The scientific curiosity to understand the cause of a disease has led to many technological innovations. As the cost of genomic sequencing started to fall a decade ago, it opened up numerous new technologies that could provide unique insights in understanding disease biology even at a molecular level. These include whole genome data (genomics), changes in the structure of chromatin, understanding RNA sequences and their expression (transcriptomics) to proteomics-based approaches to understand protein structure, folding and the measurement of various metabolites (metabolomics). These broad array of technological advancements have helped in deciphering causal factors thus enhancing our ability to study and insight into many diseases through different dimensions and resolutions which were not previously possible.

A fundamental challenge in biomedical research is to identify accurate, early indicators of a disease. Recent advances in sequencing technologies have led to unparalleled efforts to characterize the molecular changes that underlie the development and progression of complex human diseases, including cancer. Scientists have widely used RNA-seq analysis to study the transcriptome in populations of cells. More recently, single-cell RNA seq studies have been used to gain insight on cellular traits and changes in cellular state.

Single-cell genomics techniques are revolutionizing our ability to characterize complex tissues. Although bulk RNA sequencing experiments can be insightful, they often mask important biological activity of rare cell types and fail to show the variability in gene expression between individual cells. The rapid development of low-input RNA seq methods has led to an explosion of single-cell RNA-seq platforms, each with their own advantages and limitations. Droplet-based methods (10X Chromium, DropSeq) can be used to analyze thousands of cells in a single prep. In this method, single cells are separated using microfluidics.

In 2013, single-cell sequencing was selected as the method of the year to highlight its ability to sequence DNA and RNA in individual cells. The advantages of such high-resolution sequencing are to unveil previously unknown cell population heterogeneity and to perform more accurate analysis. The high degree of heterogeneity in tumor tissue is widely considered to relate to the mechanisms of tumorigenesis and metastasis. Traditional sequencing methods can only detect cell populations then get the average of the signals in a group of cells. Now with the help of single-cell sequencing and analysis, researchers can explore the heterogeneity among individual cells, detect rare cell types, study immune process and do much more.