A Systematic Literature Review of Comparative Visualization Designs and Techniques for Comparative Genomics Analysis

Visual analytics are vital in helping people understand and make sense of the data. Visualizing genome sequencing data is especially important to comparative genomics analysis, particularly to wildlife and botanical forensics, environment DNA (eDNA) monitoring, species evolutionary history investigation in a specific population, and the establishment of conservation planning. Despite the advancement of computing technologies to provide instantly aggregated statistical or similarity measures, humans often rely on visual perception to identify the distinction between the genomic sequences to answer biological questions, such as where the gene rearrangement between sequences is and which position of nucleotide mutated. Hence, comparative visualization considerations are crucial to designing effective visual analytical tools that exploit the human perception system to help people consume and understand a significant amount of data with complex relationships. In this context, the rationale of this paper is to study visualization techniques and tools for comparative genomics analysis. It includes the identification of comparative genomics visualization techniques, systematic mapping of comparative visualization design considerations, and investigation of evaluation methods suited for studying the effectiveness and efficiency of comparative visualization tools. This work employs evidence-based software engineering (EBSE) methodology for this systematic literature review and meta-analysis. The authors anticipate that this work can contribute to the knowledge gaps of visualization design and evaluation and open more opportunities for future study in various domains that require comparative analysis.