Single-Cell RNA Sequencing Analysis - Machine Learning for Bioinformatics Project - Sharif University of Technology (SUT) - Prof. Ali Sharifi-Zarchi - Spring 2023 (1401-2)

Single-cell RNA sequencing (scRNA-seq) is a powerful technique used in molecular biology to study gene expression at the single-cell level. It allows researchers to profile the transcriptome of individual cells, providing insights into cellular heterogeneity and identifying distinct cell types within a tissue or sample.

By analyzing gene expression at the single-cell level, scRNA-seq enables researchers to gain insights into the diversity of cell types, identify rare cell populations, characterize cell states, and study cellular dynamics in various biological processes, such as development, disease progression, or response to treatments.

It's important to note that scRNA-seq is a rapidly evolving field, and new methods and technologies are continuously being developed to improve sensitivity, throughput, and the ability to capture additional molecular features beyond gene expression, such as chromatin accessibility or protein levels.

In this project, you are going to get familiar with the general steps of analyzing scRNA-seq data, through different steps of preprocessing and clustering.