Results 1 to 10 of about 86,859 (350)

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

ScRNA-Seq Deciphers an Autocrine EFNA1-EPHA1 Loop That Reprograms the Microenvironment in Hepatocellular Carcinoma. [PDF]

J Hepatocell Carcinoma
Chen Y, Tang Y, Ning Y, Yang Y, Tian R, Mao Y, Feng Z, Lin W, Wang D, Feng X.   +9 more
europepmc   +3 more sources

scDrug: From single-cell RNA-seq to drug response prediction

Computational and Structural Biotechnology Journal, 2023
Single-cell RNA sequencing (scRNA-seq) technology allows massively parallel characterization of thousands of cells at the transcriptome level. scRNA-seq is emerging as an important tool to investigate the cellular components and their interactions in the
Chiao-Yu Hsieh, Jian-Hung Wen, Shih-Ming Lin, Tzu-Yang Tseng, Jia-Hsin Huang, Hsuan-Cheng Huang, Hsueh-Fen Juan   +6 more
doaj   +1 more source

Microfluidics Facilitates the Development of Single-Cell RNA Sequencing

Biosensors, 2022
Single-cell RNA sequencing (scRNA-seq) technology provides a powerful tool for understanding complex biosystems at the single-cell and single-molecule level.
Yating Pan, Wenjian Cao, Ying Mu, Qiangyuan Zhu   +3 more
doaj   +1 more source

RFCell: A Gene Selection Approach for scRNA-seq Clustering Based on Permutation and Random Forest

Frontiers in Genetics, 2021
In recent years, the application of single cell RNA-seq (scRNA-seq) has become more and more popular in fields such as biology and medical research. Analyzing scRNA-seq data can discover complex cell populations and infer single-cell trajectories in cell
Yuan Zhao, Zhao-Yu Fang, Cui-Xiang Lin, Chao Deng, Yun-Pei Xu, Hong-Dong Li   +5 more
doaj   +1 more source

scRNA‐seq data analysis method to improve analysis performance

IET Nanobiotechnology, 2023
With the development of single‐cell RNA sequencing technology (scRNA‐seq), we have the ability to study biological questions at the level of the individual cell transcriptome.
Junru Lu, Yuqi Sheng, Weiheng Qian, Min Pan, Xiangwei Zhao, Qinyu Ge   +5 more
doaj   +1 more source

Revealing cell fate decisions during reprogramming by scRNA-seq [PDF]

E3S Web of Conferences, 2020
Single-cell RNA sequencing (scRNA-seq) technologies serve as powerful tools to dissect cellular heterogeneity comprehensively. With the rapid development of scRNA-seq, many previously unsolved questions were answered by using scRNA-seq.
Liang Yu
doaj   +1 more source

The Application of Single-Cell RNA Sequencing in Mammalian Meiosis Studies

Frontiers in Cell and Developmental Biology, 2021
Meiosis is a cellular division process that produces gametes for sexual reproduction. Disruption of complex events throughout meiosis, such as synapsis and homologous recombination, can lead to infertility and aneuploidy.
Yiheng Peng, Huanyu Qiao
doaj   +1 more source

scDEcrypter: Uncertainty-aware differential expression analysis for viral infection in scRNA-seq [PDF]

bioRxiv
Luer Zhong, Karl Ensberg, Scott Tibbets, Aaron J. Molstad, Rhonda Bacher   +4 more
europepmc   +3 more sources