Hamed Zeinalzadeh

Hamed Zeinalzadeh

ML Engineer

© 2025

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Single-Cell RNA Sequencing Analysis
Jan 9, 2025
  • Bioinformatics

Introduction to Single-Cell RNA Sequencing (scRNA-seq)

Single-cell RNA sequencing (scRNA-seq) is a groundbreaking technique in molecular biology designed to study gene expression at the individual cell level. Unlike traditional bulk RNA sequencing, which averages gene expression across a population of cells, scRNA-seq provides a high-resolution view of the transcriptome for each cell. This enables researchers to uncover cellular heterogeneity and identify distinct cell types within a complex tissue or sample.

Key Benefits of scRNA-seq

  • Cellular Heterogeneity: scRNA-seq reveals the diversity of cell types and states within a sample.
  • Rare Cell Populations: It enables the identification of rare or previously unknown cell types.
  • Dynamic Processes: Researchers can characterize how cells transition between states during biological processes such as development, disease progression, or treatment response.

Advancements in the Field

The field of scRNA-seq is rapidly evolving. New methods and technologies are continually being developed to enhance:

  • Sensitivity: Capturing low-abundance transcripts more effectively.
  • Throughput: Analyzing thousands or even millions of cells in a single experiment.
  • Multimodal Analysis: Integrating additional molecular features like chromatin accessibility or protein levels alongside gene expression.

This Project

In this project, you will explore the general steps involved in analyzing scRNA-seq data, focusing on two main components:

  1. Preprocessing and Clustering: Learn the foundational steps of scRNA-seq analysis, such as quality control, normalization, and dimensionality reduction, followed by clustering to group similar cells.
  2. Individual Research Topic: Select and propose a specific topic for detailed analysis. Suggested topics and guidelines will be provided at the end of this document.

To gain a strong understanding of scRNA-seq data analysis, we highly recommend the following tutorial:

  • Current Best Practices in Single-Cell RNA-Seq Analysis: A Tutorial by Malte D. Luecken & Fabian J. Theis (2019)

This resource offers a comprehensive overview of state-of-the-art techniques and best practices in the field.