Improving accuracy in genomic mapping with time-series data
If you already have the sequenced map of an organism's genome but want to look for structural oddities in a sample, you can check the genomic barcode—a series of distances between known, targeted sites—by cutting a DNA sequence at those sites and examining the distance between the cuts. However, if the original map—obtained through next-generation sequencing involving PCR—contains any amplification biases, there is room for systematic error across studies. To remedy this, researchers at the University of Minnesota and BioNano Genomics have improved a nanochannel-based form of mapping by using dynamic time-series data to measure the probability distribution, or how much genetic material separates two labels, based on whether the strands are stretched or compressed.