Authors:
Cassisa Anna
1
;
2
;
Jamal Elhasnaoui
1
;
2
;
Uliveto Chiara
1
;
2
;
Riccardo Corsi
3
;
Elena Grassi
1
;
2
;
Dalibor Stuchlík
4
;
Livio Trusolino
1
;
2
;
Aleš Křenek
4
;
Luca Vezzadini
3
;
Andrea Bertotti
1
;
2
;
Claudio Isella
1
;
2
and
Enzo Medico
1
;
2
Affiliations:
1
University of Torino, Department of Oncology, Candiolo, Torino, 10060, Italy
;
2
Candiolo Cancer Institute, Fondazione Piemontese per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, 10060, Italy
;
3
Kairos3D, via Agostino da Montefeltro 2, 10134, Turin, Italy
;
4
Institute of Computer Science, Masaryk University, Šumavská 15, 60200, Brno, Czech Republic
Keyword(s):
GenomeCruzer, Genomic Landscape, View Mode, Graphical Metaphors, Multidimensional Omics, Colorectal Cancer, Breast Cancer.
Abstract:
The development of high-throughput sequencing technologies has generated vast amounts of multi-layered molecular data from human tumours, but effectively visualizing and analysing these complex datasets remains a significant challenge for researchers. We introduce GenomeCruzer, a software designed to enable real-time, interactive visualization and analysis of large, multi-layer genomic and clinical data. GenomeCruzer uses graphical metaphors to represent continuous variables like gene expression, DNA methylation, and copy number alterations (CNA) through 3D objects with varying colour, size, and transparency, while discrete variables are represented by highlighting or blinking. We applied GenomeCruzer to DNA methylation and DNA/RNA sequencing data from colorectal cancer (CRC) samples from The Cancer Genome Atlas (TCGA) and CRC Patient-Derived Xenografts (PDXs). The software successfully generated 3D landscapes, allowing intuitive exploration of associations between omic profiles and
clinical features. GenomeCruzer demonstrates its utility in highlighting subgroup differences, selecting representative cases, annotating samples, and identifying relationships between sample groups and gene signatures. Its intuitive interface and ability to visualize complex data make it a valuable tool for biomedical research.
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