Katalog Plus
Bibliothek der Frankfurt UAS
Bald neuer Katalog: sichern Sie sich schon vorab Ihre persönlichen Merklisten im Nutzerkonto: Anleitung.
Dieses Ergebnis aus BASE kann Gästen nicht angezeigt werden.  Login für vollen Zugriff.

FUSION: A web-based application for in-depth exploration of multi-omics data with brightfield histology

Title: FUSION: A web-based application for in-depth exploration of multi-omics data with brightfield histology
Authors: Border, Samuel; Ferreira, Ricardo Melo; Lucarelli, Nicholas; Manthey, David; Kumar, Suhas; Paul, Anindya; Mimar, Sayat; Naglah, Ahmed; Cheng, Ying-Hua; Barisoni, Laura; Ray, Jessica; Strekalova, Yulia; Rosenberg, Avi Z.; Tomaszewski, John E.; Hodgin, Jeffrey B.; HuBMAP consortium; El-Achkar, Tarek M.; Jain, Sanjay; Eadon, Michael T.; Sarder, Pinaki
Contributors: Medicine, School of Medicine
Source: PMC
Publisher Information: bioRxiv
Publication Year: 2024
Collection: Indiana University - Purdue University Indianapolis: IUPUI Scholar Works
Subject Terms: Histopathology; Tissue microenvironment; Molecular profiles
Description: Spatial -OMICS technologies facilitate the interrogation of molecular profiles in the context of the underlying histopathology and tissue microenvironment. Paired analysis of histopathology and molecular data can provide pathologists with otherwise unobtainable insights into biological mechanisms. To connect the disparate molecular and histopathologic features into a single workspace, we developed FUSION (Functional Unit State IdentificatiON in WSIs [Whole Slide Images]), a web-based tool that provides users with a broad array of visualization and analytical tools including deep learning-based algorithms for in-depth interrogation of spatial -OMICS datasets and their associated high-resolution histology images. FUSION enables end-to-end analysis of functional tissue units (FTUs), automatically aggregating underlying molecular data to provide a histopathology-based medium for analyzing healthy and altered cell states and driving new discoveries using "pathomic" features. We demonstrate FUSION using 10x Visium spatial transcriptomics (ST) data from both formalin-fixed paraffin embedded (FFPE) and frozen prepared datasets consisting of healthy and diseased tissue. Through several use-cases, we demonstrate how users can identify spatial linkages between quantitative pathomics, qualitative image characteristics, and spatial --omics.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: https://hdl.handle.net/1805/43455
Availability: https://hdl.handle.net/1805/43455
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International ; http://creativecommons.org/licenses/by-nc-nd/4.0/
Accession Number: edsbas.67954FB1
Database: BASE