Results 41 to 50 of about 17,437 (131)
Single-nucleus and single-cell transcriptomes compared in matched cortical cell types.
Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based
Trygve E Bakken +27 more
doaj +1 more source
The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non‐parenchymal cells. Recent advances in single‐cell transcriptional approaches have enabled an examination of the human liver with ...
Tallulah S. Andrews +19 more
doaj +1 more source
Accurate sample deconvolution of pooled snRNA-seq using sex-dependent gene expression patterns. [PDF]
Summary Single-nucleus RNA sequencing (snRNA-seq) technology offers unprecedented resolution for studying cell type-specific gene expression patterns. However, snRNA-seq poses high costs and technical limitations, often requiring the pooling of independent biological samples and the loss of individual sample-level data. Deconvolution of
Twa GM +3 more
europepmc +4 more sources
Quality control analysis for 10X snRNA-seq v2
Here we describe a computational protocol for performing quality control analysis on shallow sequencing data obtained from 10X snRNA-seq experiments. The workflow starts with raw MiSeq run folders and uses cellranger to generate count matrices. The raw count matrices are analyzed and sequencing saturation plots are generated.
openaire +1 more source
Quality control analysis for 10X snRNA-seq v1
Here we describe a computational protocol for performing quality control analysis on shallow sequencing data obtained from 10X snRNA-seq experiments. The workflow starts with raw MiSeq run folders and uses cellranger to generate count matrices. The raw count matrices are analyzed and sequencing saturation plots are generated.
openaire +1 more source
Cell Type-Aware Multiple Instance Learning Improves Alzheimer’s Disease Prediction from snRNA-seq [PDF]
Kristen Mş O'Connell, Amy R Dunn
exaly +1 more source
Single-cell and single-nuclei RNA-sequencing (scRNA-seq and snRNA-seq) analyze cell-specific transcriptomes. However, only snRNA-seq applies to frozen biobanked samples.
Karin Engström +5 more
doaj +1 more source
Summary: Caenorhabditis elegans is a valuable model to study organ, tissue, and cell-type responses to external cues. However, the nematode comprises multiple syncytial tissues with spatial coordinates corresponding to distinct nuclear transcriptomes ...
Max T. Levenson +8 more
doaj +1 more source
scREAD: A Single-Cell RNA-Seq Database for Alzheimer's Disease
Summary: Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the brain and the most common form of dementia among the elderly. The single-cell RNA-sequencing (scRNA-Seq) and single-nucleus RNA-sequencing (snRNA-Seq) techniques are ...
Jing Jiang +4 more
doaj +1 more source
A comprehensive anatomically-defined atlas of brain transcriptomics in macaques is still lacking. Here, the authors generate complementary bulk RNA-seq and snRNA-seq datasets from cynomolgus macaques to examine the link between brain-wide gene expression
Tingting Bo +12 more
doaj +1 more source

