Project Details
Description
Project Summary
In medical research, a growing number of high-content platforms and technologies are used to measure di-
verse but related information. Examples include sequencing of the genome, epigenome, transcriptome and
translatome, metabolite profiling, and imaging modalities. Moreover, data from the same high-content platform
are often measured over multiple dimensions, such as multiple tissues, body regions, or developmental time
points. We refer to data measured over multiple platforms or technologies as multi-source, and data measured
over multiple dimensions as multi-way. Many modern biomedical studies collect data that are both multi-source
and multi-way, meaning multi-way data are collected from multiple platforms. Multi-source multi-way data has
enormous potential to capture and synthesize every facet of a complex biological system. However, to date
there has been little methodology developed for fully integrative analysis of such data. We will focus on devel-
oping methods to identify biomarkers for a clinical outcome from multi-source multi-way data. Biomarkers are
often used as a surrogate for disease progression or as an endpoint for clinical trials, and so their precision
in capturing a given medical phenomenon is crucial. We propose to develop new composite biomarker meth-
ods that identify patterns across multiple sources of data, and multiple dimensions, that are associated with
a clinical outcome. Our central hypothesis is that a fully integrated and multivariate approach will yield more
precise biomarkers and simplify their interpretation. The novel product of this project will be a suite of methods
extending common biomarker tasks to the multi-source multi-way context, including dimension reduction (Aim
1a), missing value imputation (Aim 1b), high-dimensional prediction (Aim 2) and dependent hypothesis testing
(Aim 3). This work is motivated by our involvement in several ongoing collaborative translational projects with
rich multi-source multi-way data, including biomarker discovery for the development of lung cancer in chronic
obstructive pulmonary disease patients, for the progression of neurodegenerative disorders such as Friedre-
ich's Ataxia, and for brain iron deficiency in infants. We will apply and rigorously assess our multi-source
multi-way approaches on these applications. All methods will be implemented in free, open-source and easily
accessible software to facilitate their use by other researchers and practitioners.
Status | Finished |
---|---|
Effective start/end date | 3/1/19 → 11/30/23 |
Funding
- National Institute of General Medical Sciences: $269,197.00
- National Institute of General Medical Sciences: $268,956.00
- National Institute of General Medical Sciences: $268,710.00
- National Institute of General Medical Sciences: $299,367.00
- National Institute of General Medical Sciences: $299,618.00
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