Sukhadia, SS and Tyagi, A and Venkataraman, V and Mukherjee, P and Prasad, P and Gevaert, O and Nagaraj, SH (2022) ImaGene: A web-based software platform for tumor radiogenomic evaluation and reporting. In: Bioinformatics Advances, 2 (1).
|
PDF
bio_adv_2-1_2022.pdf - Published Version Download (696kB) | Preview |
Abstract
Summary: Radiographic imaging techniques provide insight into the imaging features of tumor regions of interest, while immunohistochemistry and sequencing techniques performed on biopsy samples yield omics data. Relationships between tumor genotype and phenotype can be identified from these data through traditional correlation analyses and artificial intelligence (AI) models. However, the radiogenomics community lacks a unified software platform with which to conduct such analyses in a reproducible manner. To address this gap, we developed ImaGene, a web-based platform that takes tumor omics and imaging datasets as inputs, performs correlation analysis between them, and constructs AI models. ImaGene has several modifiable configuration parameters and produces a report displaying model diagnostics. To demonstrate the utility of ImaGene, we utilized data for invasive breast carcinoma (IBC) and head and neck squamous cell carcinoma (HNSCC) and identified potential associations between imaging features and nine genes (WT1, LGI3, SP7, DSG1, ORM1, CLDN10, CST1, SMTNL2, and SLC22A31) for IBC and eight genes (NR0B1, PLA2G2A, MAL, CLDN16, PRDM14, VRTN, LRRN1, and MECOM) for HNSCC. ImaGene has the potential to become a standard platform for radiogenomic tumor analyses due to its ease of use, flexibility, and reproducibility, playing a central role in the establishment of an emerging radiogenomic knowledge base. © 2022 The Author(s). Published by Oxford University Press.
| Item Type: | Journal Article |
|---|---|
| Publication: | Bioinformatics Advances |
| Publisher: | Oxford University Press |
| Additional Information: | The copyright of this article belongs to the Authors. |
| Department/Centre: | Division of Electrical Sciences > Electrical Communication Engineering |
| Date Deposited: | 09 Mar 2023 07:06 |
| Last Modified: | 09 Mar 2023 07:06 |
| URI: | https://eprints.iisc.ac.in/id/eprint/80942 |
Actions (login required)
 |
View Item |
