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Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
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A quantitative comparison of single-cell whole genome amplification methods
Charles F A de Bourcy1, Iwijn De Vlaminck2, Jad N Kanbar3
1Department of Applied Physics, Stanford University, Stanford, California, United States of America.
Plos One
|August 20, 2014
Summary
Comparing whole genome amplification (WGA) methods for single-cell sequencing reveals significant differences in performance. The best WGA technique depends on specific experimental goals, impacting genomic heterogeneity studies.
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Single-cell sequencing is crucial for understanding genomic heterogeneity.
- Whole genome amplification (WGA) is a critical step in single-cell sequencing.
- Various WGA methods exist, necessitating comparative studies.
Purpose of the Study:
- To compare three leading WGA methods: MDA, MALBAC, and NEB-WGA.
- To evaluate WGA methods on both bulk and single-cell E. coli DNA samples.
- To assess the impact of reaction gain on coverage, errors, and contamination.
Main Methods:
- Multiple Displacement Amplification (MDA)
- Multiple Annealing and Looping Based Amplification Cycles (MALBAC)
- PicoPLEX single-cell WGA kit (NEB-WGA)
Main Results:
- No single WGA method excelled across all evaluated criteria.
- Significant differences observed in coverage uniformity, error rates, and background contamination.
- Method suitability varied for detecting copy-number variations, SNPs, and de novo genome assembly.
Conclusions:
- The choice of WGA method is highly dependent on the specific research question.
- Careful consideration of WGA method characteristics is essential for successful single-cell genomic studies.
- Comparative analysis guides optimal WGA selection for genomic heterogeneity research.
