Generally, there are 8 key parameters to characterize the performance of whole genome amplification methods, including genome coverage, uniformity, reproducibility, unmappable rates, chimera rates, allele dropout rates, false positive rates for calling single-nucleotide variations, and ability to call copy-number variations. MALBAC performs better among other whole genome amplification methods.
– Amplify single cells genome to ug level, and only need about 2-4 hrs in one single tube.
– Best amplification uniformity among other similar products, Single-Nucleotide Mismatch rate : 10^-5
– High Coverage that >90% locus can be successfully amplified, locus allele drop out <10%
– Various Applications-The amplified products can be applied for copy number variation (CNV) and single nucleotide polymorphism (SNP) analysis, pre-implantation genetic screening (PGS) and diagnosis (PGD), circulating tumor cell (CTC), etc.
The data refers to paper of Huang et al. Genomics Hum. Genet. 2015
Coefficient of variation (CV) is the key parameter for copy-number variation (CNV) analysis by next-generation sequencing, which is important for accurate measurements of CNV; Yikon’s MALBAC Single Cell WGA Kit is superior to other commercial kits regarding CV parameter with more even CNV data after normalization. This over advantage makes MALBAC Single Cell WGA Kit more suitable for clinical application, in particular for preimplantation genetic screening (PGS).
The data refers to paper of Huang et al. GenomicsHum. Genet. 2015
The allele dropout rate (ADO) is one of the most characteristics of whole genome amplification, particularly for medical application such as preimplantation genetic diagnosis (PGD). ADO is also the primary cause of false negatives of SNV calling (point mutation). MALBAC Single Cell WGA Kit has lower allele dropout rates than the other commercial kits, which indicates MALBAC Single Cell WGA Kit is the first choice for PGD and SNV analysis.
MALBAC shows better uniformity and coverage compared with MDA. (Zong et al. Science. 2012)
Higher genome coverage for haploid single cell libraries at sequencing depth of (a) 3.5 x and (b) 10.4 x. (Daley et al. Bioinformatics. 2014)
Consistent CNV analysis of circulating tumor cells. (Ni et al. PNAS. 2013)
SNP linkage analysis to infer phase information in the diploid genome (Lu et al. Science. 2012)
High and consistent mapping rates for single cells after MALBAC amplification