Calibrating genomic and allelic coverage bias in single-cell sequencing.

Nat Commun
Authors
Keywords
Abstract

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1-10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (∼0.1 × ) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples.

Year of Publication
2015
Journal
Nat Commun
Volume
6
Pages
6822
Date Published
2015 Apr 16
ISSN
2041-1723
URL
DOI
10.1038/ncomms7822
PubMed ID
25879913
PubMed Central ID
PMC4922254
Links
Grant list
P30 CA014051 / CA / NCI NIH HHS / United States
U24 CA143867 / CA / NCI NIH HHS / United States
P30-CA14051 / CA / NCI NIH HHS / United States
U24CA143867 / CA / NCI NIH HHS / United States