ArticlebioRxiv : the preprint server for biology2023
Reconstructing Spatial Transcriptomics at the Single-cell Resolution with BayesDeep.
Xi Jiang, Lei Dong, Shidan Wang, Zhuoyu Wen, Mingyi Chen, Lin Xu, Guanghua Xiao, Qiwei Li
Abstract readPreprint
In one paragraphArticle in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0citing papers in PubMed
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2 · The registryThe trial behind it
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4 · The recordCorrections and comments
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5 · Who and what moneyAuthors and funding
8 authors.
Xi JiangQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.
Lei DongQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.
Shidan WangQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.ORCID 0000-0002-0001-3261 Zhuoyu WenQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.
Mingyi ChenDepartment of Pathology, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.
Lin XuQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.
Guanghua XiaoQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.
Qiwei LiDepartment of Mathematical Sciences, The University of Texas at Dallas, Richardson, Texas, U.S.A.ORCID 0000-0002-1020-3050 Funding
Multiscale functional characterization of genomic variation in human developmental disordersUM1HG011996 · NHGRI · UT SOUTHWESTERN MEDICAL CENTER · PI Gary Chung Hon, WILLIAM Lee KRAUS · 2021 to 2026
$10.5MDeep Learning Image Analysis Algorithms to Improve Oral Cancer Risk Assessment for Oral Potentially Malignant DisordersR01DE030656 · NIDCR · YALE UNIVERSITY · PI PICKERING, CURTIS, XIAO, GUANGHUA · 2021 to 2025
$3.4MMechanisms of telomere-induced disease: Role of intestinal malabsorption, barrier dysfunction and dsybiosis.R01DK127037 · NIDDK · BAYLOR COLLEGE OF MEDICINE · PI NOAH Freeman SHROYER, Ergun Sahin · 2022 to 2026
$3.3MUnraveling ApoE4 Promotion of Cardiometabolic DiseaseR01HL144969 · NHLBI · UT SOUTHWESTERN MEDICAL CENTER · PI SHAUL, PHILIP W · 2020 to 2023
$2.6MReprogramming myeloid cells to inhibit cancer developmentR01CA263079 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI CHENGCHENG ZHANG · 2022 to 2026
$1.9MDeveloping computational algorithms for histopathological image analysisR01GM140012 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI XIAO, GUANGHUA · 2021 to 2024
$1.6MInformatics Tools To Analyze And Model Whole Slide Image Data At The Single Cell LevelU01CA249245 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI XIAO, GUANGHUA · 2021 to 2023
$1.5MDeveloping novel algorithms for spatial molecular profiling technologiesR01GM141519 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI XIAO, GUANGHUA · 2021 to 2024
$1.4MIdentifying neuroblastoma drivers and bringing them to the clinicR21CA259771 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI SKAPEK, STEPHEN X, XU, LIN · 2021 to 2021
$437kNCI NIH HHS R01 CA263079NCI NIH HHS R21 CA259771NCI NIH HHS U01 CA249245NHGRI NIH HHS UM1 HG011996NHLBI NIH HHS R01 HL144969NIDCR NIH HHS R01 DE030656NIDDK NIH HHS R01 DK127037NIGMS NIH HHS R01 GM140012NIGMS NIH HHS R01 GM141519
6 · The paper itselfAbstract
Spatially resolved transcriptomics (SRT) techniques have revolutionized the characterization of molecular profiles while preserving spatial and morphological context. However, most next-generation sequencing-based SRT techniques are limited to measuring gene expression in a confined array of spots, capturing only a fraction of the spatial domain. Typically, these spots encompass gene expression from a few to hundreds of cells, underscoring a critical need for more detailed, single-cell resolution SRT data to enhance our understanding of biological functions within the tissue context. Addressing this challenge, we introduce BayesDeep, a novel Bayesian hierarchical model that leverages cellular morphological data from histology images, commonly paired with SRT data, to reconstruct SRT data at the single-cell resolution. BayesDeep effectively model count data from SRT studies
Indexed as
Bayesian hierarchical modelCellular morphological featuresSingle-cell resolutionSpatially resolved transcriptomics
Identifiers
PMID38106214
PMCPMC10723442
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