Assessing Amplification Quality and Bias in MDA Methods Through Comparative Analysis of Short-Read Sequencing

Although high-throughput sequencing methods have greatly improved over the last few years, direct sequencing remains unfeasible when DNA quantity or quality is limited. In such instances, various whole genome or metagenome amplification (WGA) techniques can generate sufficient DNA for multiple analyses, albeit with some amplification bias. Competent WGA analysis is typically evaluated by sequence coverage, assessed through two key parameters: depth, referring to the number of reads containing each nucleotide, and breadth, indicating the proportion of nucleotides in the consensus sequence relative to the original sequence length at the obtained depth. Adequate coverage is essential for detailed genomic analysis and the detection of population variants, copy number variations (CNVs), and structural variants (SVs). This chapter outlines a pipeline for analyzing Illumina sequencing data of amplified samples compared to non-amplified samples to assess the performance of various WGA methods, starting from raw sequences.