Novel Insights into Post-Myocardial Infarction Cardiac Remodeling through Algorithmic Detection of Cell-Type Composition Shifts.

ABSTRACT:

Background

Recent advances in single cell sequencing have led to an increased focus on the role of cell-type composition in phenotypic presentation and disease progression. Cell-type composition research in the heart is challenging due to large, frequently multinucleated cardiomyocytes that preclude most single cell approaches from obtaining accurate measurements of cell composition. Our in silico studies reveal that ignoring cell type composition when calculating differentially expressed genes (DEGs) can have significant consequences. For example, a relatively small change in cell abundance of only 10% can result in over 25% of DEGs being false positives.

Methods

We have implemented an algorithmic approach that uses snRNAseq datasets as a reference to accurately calc

SUBMITTER: Gural B 

PROVIDER: S-EPMC11326268 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature