Results 11 to 20 of about 81,661 (282)

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications [PDF]

Genome Biology, 2018
Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis.
Koen Van den Berge, Fanny Perraudeau, Charlotte Soneson, Michael I. Love, Davide Risso, Jean-Philippe Vert, Mark D. Robinson, Sandrine Dudoit, Lieven Clement   +8 more
doaj   +9 more sources

Robust subspace structure discovery for cell type identification in scRNA-seq data [PDF]

BMC Bioinformatics
Single-cell RNA sequencing (scRNA-seq) technology has transformed gene expression studies by enabling analysis at the individual cell level, offering unprecedented insights into cellular heterogeneity.
Xianyong Zhou, Xindian Wei, Cheng Liu, Wenjun Shen, Ping Xuan, Si Wu, Hau-San Wong   +6 more
doaj   +2 more sources

Droplet scRNA-seq is not zero-inflated [PDF]

Nature Biotechnology, 2019
Potential users of single cell RNA-sequencing often encounter a choice between high-throughput droplet based methods and high sensitivity plate based methods. In particular there is a widespread belief that single-cell RNA-sequencing will often fail to generate measurements for particular gene, cell pairs due to molecular inefficiencies, causing data ...
Svensson, Valentine
openaire   +5 more sources

scCompass: An Integrated Multi‐Species scRNA‐seq Database for AI‐Ready [PDF]

Advanced Science
Emerging single‐cell sequencing technology has generated large amounts of data, allowing analysis of cellular dynamics and gene regulation at the single‐cell resolution.
Pengfei Wang, Wenhao Liu, Jiajia Wang, Yana Liu, Pengjiang Li, Ping Xu, Wentao Cui, Ran Zhang, Qingqing Long, Zhilong Hu, Chen Fang, Jingxi Dong, Chunyang Zhang, Yan Chen, Chengrui Wang, Guole Liu, Hanyu Xie, Yiyang Zhang, Meng Xiao, Shubai Chen, Haiping Jiang, The X‐Compass Consortium, Yiqiang Chen, Ge Yang, Shihua Zhang, Zhen Meng, Xuezhi Wang, Guihai Feng, Xin Li, Yuanchun Zhou   +29 more
doaj   +2 more sources

Benchmarking scRNA-seq copy number variation callers [PDF]

Nat Commun
AbstractCopy number variations (CNVs), the gain or loss of genomic regions, are associated with different diseases and cancer types, where they are related to tumor progression and treatment outcome. Single cell technologies offer new possibilities to measure CNVs in individual cells, allowing to assess population heterogeneity and to delineate ...
Katharina T. Schmid, Aikaterini Symeonidi, Dmytro Hlushchenko, Maria L. Richter, Maria Colomé-Tatché   +4 more
openaire   +2 more sources

Cerebro: Interactive visualization of scRNA-seq data [PDF]

Bioinformatics, 2019
AbstractSummaryDespite the growing availability of sophisticated bioinformatic methods for the analysis of single-cell RNA-seq data, few tools exist that allow biologists without bioinformatic expertise to directly visualize and interact with their own data and results.
Hillje, Roman, Pelicci, Pier Giuseppe, Luzi, Lucilla   +2 more
openaire   +2 more sources

Gene representation in scRNA-seq is correlated with common motifs at the 3′ end of transcripts

Frontiers in Bioinformatics, 2023
One important characteristic of single-cell RNA sequencing (scRNA-seq) data is its high sparsity, where the gene-cell count data matrix contains high proportion of zeros.
Xinling Li, Greg Gibson, Peng Qiu
doaj   +1 more source

SpaGE: Spatial Gene Enhancement using scRNA-seq [PDF]

Nucleic Acids Research, 2020
AbstractSingle-cell technologies are emerging fast due to their ability to unravel the heterogeneity of biological systems. While scRNA-seq is a powerful tool that measures whole-transcriptome expression of single cells, it lacks their spatial localization.
Abdelaal, Tamim, Mourragui, Soufiane, Mahfouz, Ahmed, Reinders, Marcel J.T.   +3 more
openaire   +5 more sources

Multiplexed single-cell RNA-sequencing of mouse thymic and splenic samples

STAR Protocols, 2022
Summary: Multiplexed single-cell RNA-sequencing (scRNA-seq) enables investigating several biological samples in one scRNA-seq experiment. Here, we use antibodies tagged with a hashtag oligonucleotide (Ab-HTO) to label each sample, and 10× Genomics ...
Saran Pankaew, Clémence Grosjean, Julie Quessada, Marie Loosveld, Delphine Potier, Dominique Payet-Bornet, Mathis Nozais   +6 more
doaj   +1 more source

Boosting scRNA-seq data clustering by cluster-aware feature weighting

BMC Bioinformatics, 2021
Background The rapid development of single-cell RNA sequencing (scRNA-seq) enables the exploration of cell heterogeneity, which is usually done by scRNA-seq data clustering.
Rui-Yi Li, Jihong Guan, Shuigeng Zhou
doaj   +1 more source