Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets

Abstract Deconvolution of cell mixtures in “bulk” transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq...

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Bibliographic Details
Main Authors: Sean K. Maden, Sang Ho Kwon, Louise A. Huuki-Myers, Leonardo Collado-Torres, Stephanie C. Hicks, Kristen R. Maynard
Format: Article
Language:English
Published: BMC 2023-12-01
Series:Genome Biology
Subjects:
Deconvolution
Single-cell RNA-sequencing
Single-nucleus RNA-sequencing
Cell sizes
Online Access:https://doi.org/10.1186/s13059-023-03123-4

Internet

https://doi.org/10.1186/s13059-023-03123-4

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