VarB Plus: An Integrated Tool for Visualization of Genome Variation Datasets
Permanent link to this recordhttp://hdl.handle.net/10754/244612
MetadataShow full item record
AbstractResearch on genomic sequences has been improving significantly as more advanced technology for sequencing has been developed. This opens enormous opportunities for sequence analysis. Various analytical tools have been built for purposes such as sequence assembly, read alignments, genome browsing, comparative genomics, and visualization. From the visualization perspective, there is an increasing trend towards use of large-scale computation. However, more than power is required to produce an informative image. This is a challenge that we address by providing several ways of representing biological data in order to advance the inference endeavors of biologists. This thesis focuses on visualization of variations found in genomic sequences. We develop several visualization functions and embed them in an existing variation visualization tool as extensions. The tool we improved is named VarB, hence the nomenclature for our enhancement is VarB Plus. To the best of our knowledge, besides VarB, there is no tool that provides the capability of dynamic visualization of genome variation datasets as well as statistical analysis. Dynamic visualization allows users to toggle different parameters on and off and see the results on the fly. The statistical analysis includes Fixation Index, Relative Variant Density, and Tajima’s D. Hence we focused our efforts on this tool. The scope of our work includes plots of per-base genome coverage, Principal Coordinate Analysis (PCoA), integration with a read alignment viewer named LookSeq, and visualization of geo-biological data. In addition to description of embedded functionalities, significance, and limitations, future improvements are discussed. The result is four extensions embedded successfully in the original tool, which is built on the Qt framework in C++. Hence it is portable to numerous platforms. Our extensions have shown acceptable execution time in a beta testing with various high-volume published datasets, as well as positive feedback from several researchers in the field in terms of their usability and significance.