Calibrating genomic and allelic coverage bias in single-cell sequencing

• Main Authors: Zhang, Cheng-Zhong (Author), Francis, Joshua (Author), Cornils, Hauke (Author), Jung, Joonil (Author), Maire, Cecile (Author), Ligon, Keith L. (Author), Meyerson, Matthew (Author), Adalsteinsson, Viktor A. (Contributor), Love, John C (Contributor)
• Other Authors: Massachusetts Institute of Technology. Department of Chemical Engineering (Contributor), Koch Institute for Integrative Cancer Research at MIT (Contributor)
• Format: Article
• Language: English
• Published: Nature Publishing Group, 2017-10-02T14:11:45Z.
• Subjects: Article
• Online Access: Get fulltext

 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.