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 *

213 related articles for article (PubMed ID: 29030468)

  • 1. Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data.
    Lun ATL; Calero-Nieto FJ; Haim-Vilmovsky L; Göttgens B; Marioni JC
    Genome Res; 2017 Nov; 27(11):1795-1806. PubMed ID: 29030468
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Pooling across cells to normalize single-cell RNA sequencing data with many zero counts.
    Lun AT; Bach K; Marioni JC
    Genome Biol; 2016 Apr; 17():75. PubMed ID: 27122128
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Normalization of Single-Cell RNA-Seq Data.
    Risso D
    Methods Mol Biol; 2021; 2284():303-329. PubMed ID: 33835450
    [TBL] [Abstract][Full Text] [Related]  

  • 4. SCnorm: robust normalization of single-cell RNA-seq data.
    Bacher R; Chu LF; Leng N; Gasch AP; Thomson JA; Stewart RM; Newton M; Kendziorski C
    Nat Methods; 2017 Jun; 14(6):584-586. PubMed ID: 28418000
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Improving small RNA-seq by using a synthetic spike-in set for size-range quality control together with a set for data normalization.
    Locati MD; Terpstra I; de Leeuw WC; Kuzak M; Rauwerda H; Ensink WA; van Leeuwen S; Nehrdich U; Spaink HP; Jonker MJ; Breit TM; Dekker RJ
    Nucleic Acids Res; 2015 Aug; 43(14):e89. PubMed ID: 25870415
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Exploiting single-cell expression to characterize co-expression replicability.
    Crow M; Paul A; Ballouz S; Huang ZJ; Gillis J
    Genome Biol; 2016 May; 17():101. PubMed ID: 27165153
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Spliced synthetic genes as internal controls in RNA sequencing experiments.
    Hardwick SA; Chen WY; Wong T; Deveson IW; Blackburn J; Andersen SB; Nielsen LK; Mattick JS; Mercer TR
    Nat Methods; 2016 Sep; 13(9):792-8. PubMed ID: 27502218
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Normalization of human RNA-seq experiments using chimpanzee RNA as a spike-in standard.
    Yu H; Hahn Y; Park SR; Chung SK; Jeong S; Yang I
    Sci Rep; 2016 Aug; 6():31923. PubMed ID: 27554056
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Analysis of Technical and Biological Variability in Single-Cell RNA Sequencing.
    Kim B; Lee E; Kim JK
    Methods Mol Biol; 2019; 1935():25-43. PubMed ID: 30758818
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Expression analysis of RNA sequencing data from human neural and glial cell lines depends on technical replication and normalization methods.
    Knight VB; Serrano EE
    BMC Bioinformatics; 2018 Nov; 19(Suppl 14):412. PubMed ID: 30453873
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Normalizing single-cell RNA sequencing data: challenges and opportunities.
    Vallejos CA; Risso D; Scialdone A; Dudoit S; Marioni JC
    Nat Methods; 2017 Jun; 14(6):565-571. PubMed ID: 28504683
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data.
    Jia C; Hu Y; Kelly D; Kim J; Li M; Zhang NR
    Nucleic Acids Res; 2017 Nov; 45(19):10978-10988. PubMed ID: 29036714
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Power analysis of single-cell RNA-sequencing experiments.
    Svensson V; Natarajan KN; Ly LH; Miragaia RJ; Labalette C; Macaulay IC; Cvejic A; Teichmann SA
    Nat Methods; 2017 Apr; 14(4):381-387. PubMed ID: 28263961
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Microfluidic single-cell whole-transcriptome sequencing.
    Streets AM; Zhang X; Cao C; Pang Y; Wu X; Xiong L; Yang L; Fu Y; Zhao L; Tang F; Huang Y
    Proc Natl Acad Sci U S A; 2014 May; 111(19):7048-53. PubMed ID: 24782542
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Evaluation of the External RNA Controls Consortium (ERCC) reference material using a modified Latin square design.
    Pine PS; Munro SA; Parsons JR; McDaniel J; Lucas AB; Lozach J; Myers TG; Su Q; Jacobs-Helber SM; Salit M
    BMC Biotechnol; 2016 Jun; 16(1):54. PubMed ID: 27342544
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Synthetic spike-in standards for RNA-seq experiments.
    Jiang L; Schlesinger F; Davis CA; Zhang Y; Li R; Salit M; Gingeras TR; Oliver B
    Genome Res; 2011 Sep; 21(9):1543-51. PubMed ID: 21816910
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools.
    Leshkowitz D; Feldmesser E; Friedlander G; Jona G; Ainbinder E; Parmet Y; Horn-Saban S
    PLoS One; 2016; 11(4):e0153782. PubMed ID: 27100792
    [TBL] [Abstract][Full Text] [Related]  

  • 18. BEARscc determines robustness of single-cell clusters using simulated technical replicates.
    Severson DT; Owen RP; White MJ; Lu X; Schuster-Böckler B
    Nat Commun; 2018 Mar; 9(1):1187. PubMed ID: 29567991
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Messenger RNA capture sequencing of extracellular RNA from human biofluids using a comprehensive set of spike-in controls.
    Hulstaert E; Decock A; Morlion A; Everaert C; Verniers K; Nuytens J; Nijs N; Schroth GP; Kuersten S; Gross SM; Mestdagh P; Vandesompele J
    STAR Protoc; 2021 Jun; 2(2):100475. PubMed ID: 33937877
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Normalization of low-density microarray using external spike-in controls: analysis of macrophage cell lines expression profile.
    Fardin P; Moretti S; Biasotti B; Ricciardi A; Bonassi S; Varesio L
    BMC Genomics; 2007 Jan; 8():17. PubMed ID: 17229315
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.