Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
EN
Kurumsal BaşvuruSign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User GuideGreen Science

Language

Kurumsal Başvuru

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Contact

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2026 Raw Data Library. All rights reserved.
PrivacyTermsContact
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Differential performance of strategies for single-cell whole-genome amplification

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2025

Differential performance of strategies for single-cell whole-genome amplification

0 Datasets

0 Files

en
2025
Vol 5 (4)
Vol. 5
DOI: 10.1016/j.crmeth.2025.101025

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
David Posada
David Posada

Universidade de Vigo

Verified
Nuria Estévez‐Gómez
Tamara Prieto
Laura Tomás
+5 more

Abstract

Single-cell genomics enables studying tissues and organisms at the highest resolution. However, since a cell contains a small amount of DNA, single-cell DNA sequencing (scDNA-seq) typically requires single-cell whole-genome amplification (scWGA). Unfortunately, scWGA methods introduce technical biases that complicate the interpretation of scDNA-seq data. We compared six scWGA methods, three MDA (multiple displacement amplification; GenomiPhi, REPLI-g, and TruePrime) and three non-MDA (Ampli1, MALBAC, and PicoPLEX), on 206 tumoral and 24 healthy human cells. scWGA methods performed differently depending on the parameter of interest. REPLI-g minimized regional amplification bias, while non-MDA methods showed a more uniform and reproducible amplification. Ampli1 exhibited the lowest allelic imbalance and dropout, the most accurate insertion or deletion (indel) and copy-number detection, and a low polymerase error rate. However, REPLI-g yielded higher DNA quantities, longer amplicons, and greater genome coverage. We offer a comprehensive guide for selecting a scWGA approach, outlining trade-offs that influence the interpretation of scDNA-seq data.

How to cite this publication

Nuria Estévez‐Gómez, Tamara Prieto, Laura Tomás, Pilar Alvariño, Amy Guillaumet-Adkins, Holger Heyn, Sonia Prado‐Lòpez, David Posada (2025). Differential performance of strategies for single-cell whole-genome amplification. , 5(4), DOI: https://doi.org/10.1016/j.crmeth.2025.101025.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Article

Year

2025

Authors

8

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1016/j.crmeth.2025.101025

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access