GSCIT: smart Hash Table‑based mapping equipped genome sequence coverage inspection

Abstract

The presented study is intended to propose a new tool with many quality and coverage profling algorithms for the raw NGS data. Currently, no standard tool exists to provide coverage details of the sequenced NGS data. This necessitates the development of new algorithms and software tools to facilitate functionality to users in computationally restricted environments as quickly and efectively as possible. As a solution to this, the article presents GSCIT, a GUI-based platform independent software with zero dependencies. The software is a one-stop solution for the major pre-processing stages, including adapter trimming, quality profling, and quality trimming, along with the functionalities of mapping and coverage metric calculation. GSCIT implements a novel Hash Table-based mapping algorithm that is designed to perform mapping operations with limited resources in a signifcantly shorter amount of time. To test the proposed software, 14 experiments were executed in two phases with the seven diferent genome datasets of a wide range of species. The frst phase took into account simulated sequence reads. In contrast, the second phase used sequenced real reads. From the experiments, it was found that the obtained results from simulated reads showed accurate results with an average error of 2.04% for breadth estimation and 0.14× for depth estimation. With the proposed algorithms, the software was able to deliver the coverage details in much less time than other existing algorithms that help estimate various coverage parameters and other details. In the future, the authors intend to incorporate Deep Learning-based searching techniques for coverage detection to speed up the process.