Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.09.19.304782v1?rss=1 Authors: Bebris, K., Polaka, I. Abstract: Advances in sequencing technology have led to an ever increasing amount of available short read sequencing data. This has, consequently, exacerbated the need for efficient and precise classification tools that can be used in the analysis of this data. As it stands, recent years have shown that massive leaps in performance can be achieved when it comes to approaches that are based in heuristics, and alongside these improvements there has been an ever increasing interest in applying deep learning techniques to revolutionize this classification task. We attempt to gather up these approaches and to evaluate their performance in a reproducible fashion to get a better perspective on the current state of deep learning based methods when it comes to the classification of short read sequencing data. Copy rights belong to original authors. Visit the link for more info