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Related Experiment Video

Updated: Jan 25, 2026

Target Cell Pre-enrichment and Whole Genome Amplification for Single Cell Downstream Characterization

Target Cell Pre-enrichment and Whole Genome Amplification for Single Cell Downstream Characterization

Published on: May 15, 2018

Setting Up a Single-Cell Genomic Laboratory.

Lira Mamanova¹

¹Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK. lm4@sanger.ac.uk.

Methods in Molecular Biology (Clifton, N.J.)

|April 28, 2019

Summary

This summary is machine-generated.

High-throughput RNA sequencing (RNA-seq) enables transcriptomics. This chapter provides essential recommendations for establishing a laboratory environment optimized for high-quality single-cell RNA sequencing (scRNA-seq) library preparation and data acquisition.

Keywords:

Aliquots Automation Contamination Liquid handling Musculoskeletal disorders (MSD)RNase-free Single-cell RNA-seq (scRNA-seq)

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Last Updated: Jan 25, 2026

Target Cell Pre-enrichment and Whole Genome Amplification for Single Cell Downstream Characterization

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Published on: May 15, 2018

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

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Published on: May 23, 2018

Isolation of Adipose Tissue Nuclei for Single-Cell Genomic Applications

Isolation of Adipose Tissue Nuclei for Single-Cell Genomic Applications

Published on: June 12, 2020

Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

Massive throughput RNA sequencing (RNA-seq) has transformed transcriptomics.
Decreasing costs and new protocols drive demand for single-cell RNA sequencing (scRNA-seq).
scRNA-seq differs from bulk RNA-seq, requiring specific considerations for data quality.

Purpose of the Study:

To provide recommendations for setting up a laboratory environment suitable for single-cell RNA sequencing.
To guide researchers in achieving high-quality libraries and unbiased sequencing data in scRNA-seq projects.

Main Methods:

Review of best practices for laboratory setup specific to single-cell protocols.
Consideration of unique technical requirements for handling single cells for RNA sequencing.

Main Results:

Identification of critical environmental factors for successful scRNA-seq.
Guidelines for optimizing workflows to minimize bias and maximize data integrity.

Conclusions:

A well-prepared laboratory environment is crucial for robust single-cell RNA sequencing.
Adherence to specific recommendations ensures high-quality data for downstream transcriptomic analysis.