Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges

H Nguyen, H Nguyen, D Tran, S Draghici… - Nucleic Acids …, 2024 - academic.oup.com
Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the
measurement of the expression of all genes in each individual cell contained in a sample …

CDSeq: A novel complete deconvolution method for dissecting heterogeneous samples using gene expression data

K Kang, Q Meng, I Shats, DM Umbach… - PLoS computational …, 2019 - journals.plos.org
Quantifying cell-type proportions and their corresponding gene expression profiles in tissue
samples would enhance understanding of the contributions of individual cell types to the …

Progress and challenge for computational quantification of tissue immune cells

Z Chen, A Wu - Briefings in Bioinformatics, 2021 - academic.oup.com
Tissue immune cells have long been recognized as important regulators for the
maintenance of balance in the body system. Quantification of the abundance of different …

Computational deconvolution to estimate cell type-specific gene expression from bulk data

MK Jaakkola, LL Elo - NAR genomics and bioinformatics, 2021 - academic.oup.com
Computational deconvolution is a time and cost-efficient approach to obtain cell type-
specific information from bulk gene expression of heterogeneous tissues like blood …

Rat deconvolution as knowledge miner for immune cell trafficking from toxicogenomics databases

K Morita, T Mizuno, I Azuma, Y Suzuki… - Toxicological …, 2024 - academic.oup.com
Toxicogenomics databases are useful for understanding biological responses in individuals
because they include a diverse spectrum of biological responses. Although these databases …

A computational method for direct imputation of cell type-specific expression profiles and cellular compositions from bulk-tissue RNA-Seq in brain disorders

A Doostparast Torshizi, J Duan… - NAR Genomics and …, 2021 - academic.oup.com
The importance of cell type-specific gene expression in disease-relevant tissues is
increasingly recognized in genetic studies of complex diseases. However, most gene …

The power of matrix factorization: methods for deconvoluting genetic heterogeneous data at expression level

Y Liu, Z Wen, M Li - Current Bioinformatics, 2020 - benthamdirect.com
Background: The utilization of genetic data to investigate biological problems has recently
become a vital approach. However, it is undeniable that the heterogeneity of original …

Power analysis of cell-type deconvolution methods across tissues

A Vathrakokoili Pournara, Z Miao, OY Beker, A Brazma… - bioRxiv, 2023 - biorxiv.org
Cell-type deconvolution methods aim to infer cell-type composition and the cell abundances
from bulk transcriptomic data. The proliferation of currently developed methods (> 50) …

A2Sign: Agnostic Algorithms for Signatures—a universal method for identifying molecular signatures from transcriptomic datasets prior to cell-type deconvolution

G Boldina, P Fogel, C Rocher, C Bettembourg… - …, 2022 - academic.oup.com
Motivation Molecular signatures are critical for inferring the proportions of cell types from
bulk transcriptomics data. However, the identification of these signatures is based on a …

Multivariate Curve Resolution for Analysis of Heterogeneous System in Toxicogenomics

Y Liu, J Lin, M Li, Z Wen - Machine Learning and Deep Learning in …, 2023 - Springer
The utilization of genetic data to investigate toxicological problems has become an
imperative approach. Toxicogenomics (TGx), as a specialty branch created by the merger of …