AUTHOR=Muneeb Muhammad , Feng Samuel F. , Henschel Andreas TITLE=Can We Convert Genotype Sequences Into Images for Cases/Controls Classification? JOURNAL=Frontiers in Bioinformatics VOLUME=2 YEAR=2022 URL=https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2022.914435 DOI=10.3389/fbinf.2022.914435 ISSN=2673-7647 ABSTRACT=

Converting genotype sequences into images offers advantages, such as genotype data visualization, classification, and comparison of genotype sequences. This study converted genotype sequences into images, applied two-dimensional convolutional neural networks for case/control classification, and compared the results with the one-dimensional convolutional neural network. Surprisingly, the average accuracy of multiple runs of 2DCNN was 0.86, and that of 1DCNN was 0.89, yielding a difference of 0.03, which suggests that even the 2DCNN algorithm works on genotype sequences. Moreover, the results generated by the 2DCNN exhibited less variation than those generated by the 1DCNN, thereby offering greater stability. The purpose of this study is to draw the research community’s attention to explore encoding schemes for genotype data and machine learning algorithms that can be used on genotype data by changing the representation of the genotype data for case/control classification.