CView: A network based tool for enhanced alignment visualization
Creators: name: Linheiro, Raquel
name: Sabatino, Stephen
name: Lobo, Diana
name: Archer, John
Publisher: name: Zenodo
Year: 2022

description: <strong>Conference Details: </strong> ISMB/ECCB, 10th - 14th July 2022, Virtual (url) Presenter: John Archer. <strong>Poster Abstract:</strong> To date basic visualization of sequence alignments have largely focused on displaying per-site columns of nucleotide, or amino acid, residues along with associated frequency summarizations. The persistence of this tendency to the recent tools designed for viewing mapped read data indicates that such a perspective not only provides a reliable visualization of per-site alterations, but also offers implicit reassurance to the end-user in relation to data accessibility. However, the initial insight gained is limited, something that is especially true when viewing alignments consisting of many sequences representing differing factors such as location, date and subtype. A basic alignment viewer can have potential to increase initial insight through visual enhancement, whilst not delving into the realms of complex sequence analysis. We present CView, a visualizer that expands on the per-site representation of residues through the incorporation of a dynamic network that is based on the summarization of diversity present across different regions of the alignment. Within the network, nodes are based on the clustering of sequence fragments that span windows placed consecutively along the alignment. Edges are placed between nodes of neighbouring windows where they share sequence identification(s), i.e. different regions of the same sequence(s). Thus, if a node is selected on the network, then the relationship that sequences passing through that node have to other regions of diversity within the alignment can be observed through path tracing. In addition to augmenting visual insight, CView provides export features including variant summarization, per-site residue and kmer frequencies, consensus sequence, alignment dissection as well as clustering; each useful across a range of research areas. The software has been designed to be user friendly, intuitive and interactive. It is open source and an executable jar, source code, quick start, usage tutorial and test data are available (under the GNU General Public License) from https://sourceforge.net/projects/cview/. This poster is based on our paper: “<em>CView: A network based tool for enhanced alignment visualization</em>” [1]. <strong>Tutorials</strong> 1. A demonstration of CView usage in the form of an mp4 movie is available here. 2. A demonstration of how variants can be identified using CView is available here. <strong>Case Study Data</strong> The alignment used for the case study described within the manuscript is available here. The CView project page is located at: https://sourceforge.net/projects/cview/ Related software to this project are:<br> 1. CStone<br> 2. CSReadGen<br> 3. CView &lt;<br> 4. ChimSim<br> 5. TVScript General details of the project are available here. <strong>References</strong> 1. Linheiro, R., Sabatino, S., Lobo, D., &amp; Archer, J. (2022). CView: A network based tool for enhanced alignment visualization. <em>PLOS ONE</em>, <em>17</em>(6), e0259726. https://doi.org/10.1371/JOURNAL.PONE.0259726 <strong>| linkedIn . web . orcid |</strong><br> | linheiro . web . orcid |---| sabatino . web . orcid |---| lobo . web . orcid |---| archer . web . orcid |
description: This work was funded by the project NORTE-01-0246-FEDER-000063, supported by Norte Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by research funding from the project under the references PTDC/BIA-EVF/29115/2017 and POCI-01-0145-FEDER-029115 co-funded by Operational Competitiveness and Internationalization Program, Portugal 2020 and the European Union via the European Regional Development Fund (ERDF), and by National Funds through FCT. DL was supported by FCT through a PhD grant with the reference PD/BD/132403/2017. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. FCT URL: https://www.fct.pt/.