A research team in China is developing a new genotyping method using deletion visualisation and classification. This looks at where parts of genes have been lost during DNA repair after damage. Their results showed that the approach was more accurate than earlier methods, had a wider detectable deletion length range, and was able to perform better with high and low coverage data. Tests on simulated data from a range of diseases with high levels of noise compared well against genotype “calling” methods such as Pindel and LUMPY (a probabilistic framework).
Such an approach might be useful in biomedical research into the rare muscle-wasting disease spinal muscular atrophy and the nervous system disorder “cri de chat syndrome”.
Wang, J., Gao, J. and Ling, C. (2018) ‘Deletion genotype calling on the basis of sequence visualisation and image classification’, Int. J. Data Mining and Bioinformatics, Vol. 20, No. 2, pp.109–122.