RT Journal Article
SR Electronic
T1 RESEPT: tissue architecture inference and visualization from spatially resolved transcriptomics
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.07.08.451210
DO 10.1101/2021.07.08.451210
A1 Yuzhou Chang
A1 Fei He
A1 Juexin Wang
A1 Shuo Chen
A1 Jingyi Li
A1 Jixin Liu
A1 Yang Yu
A1 Li Su
A1 Anjun Ma
A1 Carter Allen
A1 Yu Lin
A1 Shaoli Sun
A1 Bingqiang Liu
A1 Jose Otero
A1 Dongjun Chung
A1 Hongjun Fu
A1 Zihai Li
A1 Dong Xu
A1 Qin Ma
YR 2021
UL http://biorxiv.org/content/early/2021/07/09/2021.07.08.451210.abstract
AB We present RESEPT, a deep-learning framework for characterizing and visualizing tissue architecture from spatially resolved transcriptomics by reconstructing and segmenting a transcriptome mapped RGB image. RESEPT can identify the tissue architecture, and represent corresponding marker genes and biological functions accurately. RESEPT also provides critical insights into the underlying mechanisms driving the complex tissue heterogeneities in Alzheimer’s disease and glioblastoma.Competing Interest StatementThe authors have declared no competing interest.