Single-Cell Sequencing
Single-cell sequencing analyzes nucleic acid sequences from individual cells using next-generation sequencing (NGS) technologies. It provides detailed information on cellular variability and function within their microenvironment.

Applications
Single-cell sequencing analyzes nucleic acid sequences from individual cells using next-generation sequencing (NGS) technologies. It provides detailed information on cellular variability and function within their microenvironment
Single-Cell RNA Sequencing Workflow
Step 1: Generate a Single-Cell Suspension
The tissue or sample is dissociated into individual cells suspended in a solution. This step ensures each cell can be processed separately.
Step 2: Isolate Individual Cells
Single cells are isolated using methods such as Flow Cytometry (FACS) or microfluidic systems. This ensures separation and prevents cross-contamination between cells.
Step 3: Cell Barcoding and Amplification
Each cell is assigned a unique barcode to identify its RNA during sequencing. The RNA is then amplified to generate sufficient material for sequencing.
Step 4: Library Preparation and Sequencing
Barcoded RNA from all cells is pooled into a single library. The library undergoes next-generation sequencing (NGS) to capture transcriptomic data from each individual cell.
Step 5: Data Analysis
Raw sequencing reads are aligned to a reference transcriptome. Data analysis pipelines are used to quantify gene expression and identify cellular differences.

What is Single-Cell Analytics?
Single-cell analytics is a transformative approach to studying biological systems at the most granular level. By analyzing individual cells, scientists can:
Understand Cellular Heterogeneity: Discover how cells with identical DNA function differently.
Track Cellular Dynamics: Investigate cellular responses to environmental changes, disease, or therapies.
Unlock Precision Medicine: Tailor treatments based on cellular-level data for better patient outcomes.
