Friday, March 20, 2026 3/20/2026

Computational toolbox for spatial transcriptomic analysis of complex tissues

Award Number: R21HG012639
ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/21/2023
PERIOD OF PERFORMANCE END DATE: 08/31/2025

Group Awards By:

View Award Description

Computational toolbox for spatial transcriptomic analysis of complex tissues - PROJECT SUMMARY Mapping the spatial organization of cells and their communication in tissues is essential to understanding the process of development and disease formation. The rapid development of spatial transcriptomic technologies has enabled the profiling of the full transcriptome across thousands of locations in a tissue sample. In addition to transcriptional measurements, this technology also obtains paired histological imaging of the tissue. The spatially resolved profiling of gene expression has the potential to unlock groundbreaking discoveries, however, there are critical barriers in analyzing this data especially in complex tissue samples that involve the mixing of many diverse cell types in capture locations (spots). The low resolution makes it difficult to discern diverse cell types which is essential for downstream analysis of their spatial organization, dynamics, and interactions. Additionally, integrating spatial transcriptomic datasets across multiple tissue samples is not straightforward due to this technical limitation. Existing computational tools for analyzing high-dimensional genomic data were either built for single-cell resolution data or require paired single-cell transcriptomic data to guide the analysis of spatial transcriptomic data. Additionally, current methods do not consider spatial dependencies and information embedded in the histology image. The overarching goal of this proposal is to develop novel machine learning methods for analyzing the new wave of spatial transcriptomic data without the need for paired single-cell data as a reference. These innovative frameworks will enable characterizing diverse cell states and their spatial dynamics through a semi-supervised deconvolution of data (Aim 1) which will also allow integration of data from multiple tissue samples. We will also develop a multi-view framework for the integration of spatial transcriptomic and histological imaging for improved inference of intercellular interactions (Aim 2). By combining image processing algorithms for the alignment of images from replicate samples, we will extend this framework for integrating tissue samples. Our toolbox will be applicable to a broad range of tissue systems and larger clinical cohorts and has the potential to be transformative in understanding spatial dynamics during healthy development and guiding diagnosis and therapeutic strategies based on the spatial organization of cell types specific to the disease microenvironment.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $0 )
2026	2023	THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK	615 W 131ST ST	NEW YORK	NY	10027	NEW YORK	USA	Human Genome Research	000	1	3/5/2026	NEW	$0
														Subtotal = $0

Issue Date FY: 2023 ( Subtotal = $435,475 )
2023	2023	TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK, THE	202 LOW LIBRARY 535 W 116 ST MC 4309,	NEW YORK	NY	10027	NEW YORK	USA	Human Genome Research	000	1	9/21/2023	NEW	$435,475
														Subtotal = $435,475

Grand Total All Awards = $435,475

Top

All Categories

About

Search

Reports

Data Submission

Award Information

Computational toolbox for spatial transcriptomic analysis of complex tissues

Award Number: R21HG012639

ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 09/21/2023

PERIOD OF PERFORMANCE END DATE: 08/31/2025

Federal Websites

Department of Health & Human Services

HHS Operating Divisions

HHS Staff Divisions

Download A Document Viewer