These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

179 related articles for article (PubMed ID: 34824223)

  • 1. A benchmark study of simulation methods for single-cell RNA sequencing data.
    Cao Y; Yang P; Yang JYH
    Nat Commun; 2021 Nov; 12(1):6911. PubMed ID: 34824223
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Benchmarking UMI-based single-cell RNA-seq preprocessing workflows.
    You Y; Tian L; Su S; Dong X; Jabbari JS; Hickey PF; Ritchie ME
    Genome Biol; 2021 Dec; 22(1):339. PubMed ID: 34906205
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Supervised application of internal validation measures to benchmark dimensionality reduction methods in scRNA-seq data.
    Koch FC; Sutton GJ; Voineagu I; Vafaee F
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34374742
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Protocol for executing and benchmarking eight computational doublet-detection methods in single-cell RNA sequencing data analysis.
    Xi NM; Li JJ
    STAR Protoc; 2021 Sep; 2(3):100699. PubMed ID: 34382023
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The shaky foundations of simulating single-cell RNA sequencing data.
    Crowell HL; Morillo Leonardo SX; Soneson C; Robinson MD
    Genome Biol; 2023 Mar; 24(1):62. PubMed ID: 36991470
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Evaluation of Cell Type Annotation R Packages on Single-cell RNA-seq Data.
    Huang Q; Liu Y; Du Y; Garmire LX
    Genomics Proteomics Bioinformatics; 2021 Apr; 19(2):267-281. PubMed ID: 33359678
    [TBL] [Abstract][Full Text] [Related]  

  • 7. How does the structure of data impact cell-cell similarity? Evaluating how structural properties influence the performance of proximity metrics in single cell RNA-seq data.
    Watson ER; Mora A; Taherian Fard A; Mar JC
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36151725
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Benchmarking imputation methods for network inference using a novel method of synthetic scRNA-seq data generation.
    Lasri A; Shahrezaei V; Sturrock M
    BMC Bioinformatics; 2022 Jun; 23(1):236. PubMed ID: 35715748
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluation of cell-cell interaction methods by integrating single-cell RNA sequencing data with spatial information.
    Liu Z; Sun D; Wang C
    Genome Biol; 2022 Oct; 23(1):218. PubMed ID: 36253792
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios.
    Duo H; Li Y; Lan Y; Tao J; Yang Q; Xiao Y; Sun J; Li L; Nie X; Zhang X; Liang G; Liu M; Hao Y; Li B
    Genome Biol; 2024 Jun; 25(1):145. PubMed ID: 38831386
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A multi-center cross-platform single-cell RNA sequencing reference dataset.
    Chen X; Yang Z; Chen W; Zhao Y; Farmer A; Tran B; Furtak V; Moos M; Xiao W; Wang C
    Sci Data; 2021 Feb; 8(1):39. PubMed ID: 33531477
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments.
    Tian L; Dong X; Freytag S; LĂȘ Cao KA; Su S; JalalAbadi A; Amann-Zalcenstein D; Weber TS; Seidi A; Jabbari JS; Naik SH; Ritchie ME
    Nat Methods; 2019 Jun; 16(6):479-487. PubMed ID: 31133762
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A systematic evaluation of single-cell RNA-sequencing imputation methods.
    Hou W; Ji Z; Ji H; Hicks SC
    Genome Biol; 2020 Aug; 21(1):218. PubMed ID: 32854757
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Data Analysis in Single-Cell Transcriptome Sequencing.
    Gao S
    Methods Mol Biol; 2018; 1754():311-326. PubMed ID: 29536451
    [TBL] [Abstract][Full Text] [Related]  

  • 15. splatPop: simulating population scale single-cell RNA sequencing data.
    Azodi CB; Zappia L; Oshlack A; McCarthy DJ
    Genome Biol; 2021 Dec; 22(1):341. PubMed ID: 34911537
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A comparison of marker gene selection methods for single-cell RNA sequencing data.
    Pullin JM; McCarthy DJ
    Genome Biol; 2024 Feb; 25(1):56. PubMed ID: 38409056
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comparative Analysis of Single-Cell RNA Sequencing Methods.
    Ziegenhain C; Vieth B; Parekh S; Reinius B; Guillaumet-Adkins A; Smets M; Leonhardt H; Heyn H; Hellmann I; Enard W
    Mol Cell; 2017 Feb; 65(4):631-643.e4. PubMed ID: 28212749
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data.
    Xi NM; Li JJ
    Cell Syst; 2021 Feb; 12(2):176-194.e6. PubMed ID: 33338399
    [TBL] [Abstract][Full Text] [Related]  

  • 19. CaSTLe - Classification of single cells by transfer learning: Harnessing the power of publicly available single cell RNA sequencing experiments to annotate new experiments.
    Lieberman Y; Rokach L; Shay T
    PLoS One; 2018; 13(10):e0205499. PubMed ID: 30304022
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data.
    Yu L; Cao Y; Yang JYH; Yang P
    Genome Biol; 2022 Feb; 23(1):49. PubMed ID: 35135612
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.