Page 62 - TD-2-2

Tumor Discovery

PERSPECTIVE ARTICLE
Structural variants integration and

visualization: A comprehensive R package for
integration of somatic structural variations from

multiple callers and visualization

2†
3
1,2
Lei Yu 1,2† *, Le Zhang , Lili Wang , and Zhenyu Jia *
1 Department of Botany and Plant Sciences, University of California, Riverside, California, USA
2 Graduate Program in Genetics, Genomics, and Bioinformatics, University of California, Riverside,
California, USA
3 Department of Systems Biology, Beckman Research Institute, Monrovia, California, USA

Abstract

Whole genome sequencing (WGS) emerges as a powerful tool for detecting structural
variations (SVs) in genomes. However, different SV callers can produce variable
results due to the distinct rationale and sensitivity of pipelines, highlighting the need
for effective tools to compare and merge results from multiple callers. Here, we
developed an R package, structural variants integration and visualization, to facilitate
† These authors contributed equally the integration, classification, and visualization of SV results from multiple callers,
to this work. allowing for accurate identification of the most reliable SVs. Our package relies on
*Corresponding authors: a complex translocation projection and clustering method, enabling the projection
Lei Yu of each translation to a point in a Cartesian coordinate system and visualization of
(lyu062@ucr.edu) SVs at both whole-genome and individual chromosome levels. Thus, our approach
Zhenyu Jia
(zhenyuj@ucr.edu) provides a valuable framework for analyzing SVs from WGS data, improving the
accuracy and efficiency of SV detection, and enhancing the potential of WGS for
Citation: Yu L, Zhang L, Wang L,
et al., 2023, Structural variants clinical and research applications.
integration and visualization:
A comprehensive R package for
integration of somatic structural Keywords: Structure variation manipulation; Structure variation visualization; Structure
variations from multiple callers and variation analysis
visualization. Tumor Discov,
2(2): 0894.
https://doi.org/10.36922/td.0894
Received: May 4, 2023
Accepted: July 3, 2023 1. Introduction
Published Online: July 20, 2023
Structural variation (SV) is a type of genomic alteration commonly found in cancer,
Copyright: © 2023 Author(s). including deletions (DEL), insertions (INS), inversions (INV), duplications (DUP),
This is an Open Access article and translocations (each translocation can be noted by a pair of breakends) . These
[1]
distributed under the terms of the
Creative Commons Attribution alterations can impact the function of genes and regulatory elements, leading to
License, permitting distribution, changes in cell growth and division that may contribute to cancer development
and reproduction in any medium, and progression [2,3] . Examples of SVs associated with cancer include chromosomal
provided the original work is
properly cited. rearrangements such as the BCR-ABL fusion gene in chronic myelogenous leukemia
(CML) [4,5] , gene amplifications such as the HER2 gene in breast cancer , and gene DEL
[6]
Publisher’s Note: AccScience
[7]
[2]
Publishing remains neutral with such as the CDKN2A gene in pancreatic cancer , and many others .
regard to jurisdictional claims in
published maps and institutional Whole genome sequencing (WGS) technology can identify SVs by analyzing
affiliations. the sequence reads and their alignments through computational pipelines. The most
Volume 2 Issue 2 (2023) 1 https://doi.org/10.36922/td.0894