Bayesian estimation of cell type–specific gene expression with prior derived from single-cell data
When assessed over a large number of samples, bulk RNA sequencing provides reliable
data for gene expression at the tissue level. Single-cell RNA sequencing (scRNA-seq) …
data for gene expression at the tissue level. Single-cell RNA sequencing (scRNA-seq) …
Using multiple measurements of tissue to estimate subject-and cell-type-specific gene expression
Motivation Patterns of gene expression, quantified at the level of tissue or cells, can inform
on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression …
on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression …
A Bayesian inference transcription factor activity model for the analysis of single-cell transcriptomes
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful experimental
approach to study cellular heterogeneity. One of the challenges in scRNA-seq data analysis …
approach to study cellular heterogeneity. One of the challenges in scRNA-seq data analysis …
Using LLMs and Explainable ML to Analyze Biomarkers at Single-Cell Level for Improved Understanding of Diseases
J Elsborg, M Salvatore - Biomolecules, 2023 - mdpi.com
Single-cell RNA sequencing (scRNA-seq) technology has significantly advanced our
understanding of the diversity of cells and how this diversity is implicated in diseases. Yet …
understanding of the diversity of cells and how this diversity is implicated in diseases. Yet …
scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies
Background The rapid accumulation of single-cell RNA sequencing (scRNA-seq) data
presents unique opportunities to decode the genetically mediated cell-type specificity in …
presents unique opportunities to decode the genetically mediated cell-type specificity in …
Optimizing expression quantitative trait locus mapping workflows for single-cell studies
Background Single-cell RNA sequencing (scRNA-seq) has enabled the unbiased, high-
throughput quantification of gene expression specific to cell types and states. With the cost of …
throughput quantification of gene expression specific to cell types and states. With the cost of …
Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) provides unique insights into the pathology and
cellular origin of disease. We introduce single-cell disease relevance score (scDRS), an …
cellular origin of disease. We introduce single-cell disease relevance score (scDRS), an …
Identifying disease-critical cell types and cellular processes across the human body by integration of single-cell profiles and human genetics
Genome-wide association studies (GWAS) provide a powerful means to identify loci and
genes contributing to disease, but in many cases the related cell types/states through which …
genes contributing to disease, but in many cases the related cell types/states through which …
BCseq: accurate single cell RNA-seq quantification with bias correction
With rapid technical advances, single cell RNA-seq (scRNA-seq) has been used to detect
cell subtypes exhibiting distinct gene expression profiles and to trace cell transitions in …
cell subtypes exhibiting distinct gene expression profiles and to trace cell transitions in …
An efficient and flexible method for deconvoluting bulk RNA-seq data with single-cell RNA-seq data
Estimating cell type compositions for complex diseases is an important step to investigate
the cellular heterogeneity for understanding disease etiology and potentially facilitate early …
the cellular heterogeneity for understanding disease etiology and potentially facilitate early …