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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Related Experiment Video

Updated: Apr 5, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Single-cell ATAC-seq: strength in numbers.

Sebastian Pott¹, Jason D Lieb²

¹Department of Human Genetics, The University of Chicago, 920 E. 58th Street, Chicago, IL, 60637, USA. spott@uchicago.edu.

|August 22, 2015

Summary

This summary is machine-generated.

Single-cell ATAC-seq reveals open chromatin in individual cells. Combining sparse data from many cells helps identify factors driving cell-to-cell chromatin differences.

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Last Updated: Apr 5, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

ATAC-Seq Optimization for Cancer Epigenetics Research

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Published on: June 30, 2022

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Published on: November 13, 2017

Area of Science:

Genomics
Epigenetics
Molecular Biology

Background:

Single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) is a powerful technique for profiling chromatin accessibility at the individual cell level.
Current scATAC-seq datasets are often characterized by sparsity, posing challenges for robust analysis.
Understanding cell-to-cell variation in chromatin accessibility is crucial for deciphering cell identity and function.

Purpose of the Study:

To explore methods for overcoming data sparsity in single-cell ATAC-seq datasets.
To identify key determinants that contribute to variations in chromatin accessibility between individual cells.

Main Methods:

Utilized computational approaches to aggregate and analyze sparse single-cell ATAC-seq data.
Applied statistical models to identify significant patterns of chromatin variation across a population of cells.

Main Results:

Demonstrated that combining data from numerous single cells can effectively mitigate sparsity.
Successfully identified specific genomic regions and regulatory elements associated with cell-to-cell chromatin heterogeneity.

Conclusions:

Data integration strategies are effective in enhancing the resolution of single-cell ATAC-seq studies.
This approach facilitates the discovery of novel insights into the epigenetic underpinnings of cellular diversity.