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1
Intro
2
Bulk vs. Single-Cell
3
Why Single Cells
4
scRNA-seq Technologies
5
scRNA-seq Biological Questions
6
84k cells from 48 individuals
7
Cleaning up Data
8
Clustering and Cell Annotation
9
DEGs Gene Expression Changes with Phenotypes
10
Multi-Region Analysis
11
Module Analysis
12
Q1: Why Modules instead of single-genes
13
Q2: Difference from Bulk
14
Q3: Robustness and Reproducibility
15
Linked Regions Correlation
16
Discrepancies between Phenotype and Transcriptome
17
scRNA-seq Analysis Questions
18
Cell-Projected Phenotypes
Description:
Dive into the world of single-cell analysis in this comprehensive lecture. Explore the differences between bulk and single-cell approaches, understanding the importance of studying individual cells. Learn about various scRNA-seq technologies and their applications in addressing biological questions. Follow the analysis of 84,000 cells from 48 individuals, covering data cleaning, clustering, and cell annotation techniques. Discover how to identify differentially expressed genes and track gene expression changes associated with phenotypes. Examine multi-region analysis, module analysis, and the advantages of using modules over single genes. Address questions about robustness, reproducibility, and discrepancies between phenotype and transcriptome. Gain insights into linked regions correlation and cell-projected phenotypes, equipping yourself with essential knowledge for conducting scRNA-seq analysis.

Single Cell Analysis in Computational Biology - Lecture 3

Manolis Kellis
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