TY - JOUR
T1 - Genome U-Plot
T2 - A whole genome visualization
AU - Gaitatzes, Athanasios
AU - Johnson, Sarah H.
AU - Smadbeck, James B.
AU - Vasmatzis, George
N1 - Funding Information:
This study was partially funded by the Mayo Clinic Center for Individualized Medicine and the Mayo Clinic Genomics Systems Unit.
Publisher Copyright:
© The Author(s) 2017. Published by Oxford University Press. All rights reserved.
PY - 2018/5/15
Y1 - 2018/5/15
N2 - Motivation The ability to produce and analyze whole genome sequencing (WGS) data from samples with structural variations (SV) generated the need to visualize such abnormalities in simplified plots. Conventional two-dimensional representations of WGS data frequently use either circular or linear layouts. There are several diverse advantages regarding both these representations, but their major disadvantage is that they do not use the two-dimensional space very efficiently. We propose a layout, termed the Genome U-Plot, which spreads the chromosomes on a two-dimensional surface and essentially quadruples the spatial resolution. We present the Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities. We compare conventional visualization schemas with the Genome U-Plot using visualization metrics such as number of line crossings and crossing angle resolution measures. Based on our metrics, we improve the readability of the resulting graph by at least 2-fold, making apparent important features and making it easy to identify important genomic changes. Results A whole genome visualization tool with high spatial resolution and improved aesthetic qualities. Availability and implementation An implementation and documentation of the Genome U-Plot is publicly available at https://github.com/gaitat/GenomeUPlot.
AB - Motivation The ability to produce and analyze whole genome sequencing (WGS) data from samples with structural variations (SV) generated the need to visualize such abnormalities in simplified plots. Conventional two-dimensional representations of WGS data frequently use either circular or linear layouts. There are several diverse advantages regarding both these representations, but their major disadvantage is that they do not use the two-dimensional space very efficiently. We propose a layout, termed the Genome U-Plot, which spreads the chromosomes on a two-dimensional surface and essentially quadruples the spatial resolution. We present the Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities. We compare conventional visualization schemas with the Genome U-Plot using visualization metrics such as number of line crossings and crossing angle resolution measures. Based on our metrics, we improve the readability of the resulting graph by at least 2-fold, making apparent important features and making it easy to identify important genomic changes. Results A whole genome visualization tool with high spatial resolution and improved aesthetic qualities. Availability and implementation An implementation and documentation of the Genome U-Plot is publicly available at https://github.com/gaitat/GenomeUPlot.
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U2 - 10.1093/bioinformatics/btx829
DO - 10.1093/bioinformatics/btx829
M3 - Article
C2 - 29281001
AN - SCOPUS:85047064990
SN - 1367-4803
VL - 34
SP - 1629
EP - 1634
JO - Bioinformatics
JF - Bioinformatics
IS - 10
ER -