Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo

Lahnemann D, Koster J, Fischer U, Borkhardt A, McHardy AC, Schönhuth A (2021)
Nature Communications 12(1): 6744.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
OA 1.35 MB
Autor*in
Lahnemann, David; Koster, Johannes; Fischer, Ute; Borkhardt, Arndt; McHardy, Alice C; Schönhuth, AlexanderUniBi
Abstract / Bemerkung
Accurate single cell mutational profiles can reveal genomic cell-to-cell heterogeneity. However, sequencing libraries suitable for genotyping require whole genome amplification, which introduces allelic bias and copy errors. The resulting data violates assumptions of variant callers developed for bulk sequencing. Thus, only dedicated models accounting for amplification bias and errors can provide accurate calls. We present ProSolo for calling single nucleotide variants from multiple displacement amplified (MDA) single cell DNA sequencing data. ProSolo probabilistically models a single cell jointly with a bulk sequencing sample and integrates all relevant MDA biases in a site-specific and scalable-because computationally efficient-manner. This achieves a higher accuracy in calling and genotyping single nucleotide variants in single cells in comparison to state-of-the-art tools and supports imputation of insufficiently covered genotypes, when downstream tools cannot handle missing data. Moreover, ProSolo implements the first approach to control the false discovery rate reliably and flexibly. ProSolo is implemented in an extendable framework, with code and usage at: https://github.com/prosolo/prosolo. © 2021. The Author(s).
Erscheinungsjahr
2021
Zeitschriftentitel
Nature Communications
Band
12
Ausgabe
1
Art.-Nr.
6744
eISSN
2041-1723
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Universität Bielefeld gefördert.
Page URI
https://pub.uni-bielefeld.de/record/2959624

Zitieren

Lahnemann D, Koster J, Fischer U, Borkhardt A, McHardy AC, Schönhuth A. Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo. Nature Communications. 2021;12(1): 6744.
Lahnemann, D., Koster, J., Fischer, U., Borkhardt, A., McHardy, A. C., & Schönhuth, A. (2021). Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo. Nature Communications, 12(1), 6744. https://doi.org/10.1038/s41467-021-26938-w
Lahnemann, David, Koster, Johannes, Fischer, Ute, Borkhardt, Arndt, McHardy, Alice C, and Schönhuth, Alexander. 2021. “Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo”. Nature Communications 12 (1): 6744.
Lahnemann, D., Koster, J., Fischer, U., Borkhardt, A., McHardy, A. C., and Schönhuth, A. (2021). Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo. Nature Communications 12:6744.
Lahnemann, D., et al., 2021. Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo. Nature Communications, 12(1): 6744.
D. Lahnemann, et al., “Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo”, Nature Communications, vol. 12, 2021, : 6744.
Lahnemann, D., Koster, J., Fischer, U., Borkhardt, A., McHardy, A.C., Schönhuth, A.: Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo. Nature Communications. 12, : 6744 (2021).
Lahnemann, David, Koster, Johannes, Fischer, Ute, Borkhardt, Arndt, McHardy, Alice C, and Schönhuth, Alexander. “Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo”. Nature Communications 12.1 (2021): 6744.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Creative Commons Namensnennung 4.0 International Public License (CC-BY 4.0):
Volltext(e)
Access Level
OA Open Access
Zuletzt Hochgeladen
2022-10-17T06:12:56Z
MD5 Prüfsumme
68f3db7195522e5521a18e0931f34dd8

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Quellen

PMID: 34795237
PubMed | Europe PMC

Suchen in

Google Scholar