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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.