BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

251 related articles for article (PubMed ID: 37415108)

  • 1. scQCEA: a framework for annotation and quality control report of single-cell RNA-sequencing data.
    Nassiri I; Fairfax B; Lee A; Wu Y; Buck D; Piazza P
    BMC Genomics; 2023 Jul; 24(1):381. PubMed ID: 37415108
    [TBL] [Abstract][Full Text] [Related]  

  • 2. popsicleR: A R Package for Pre-processing and Quality Control Analysis of Single Cell RNA-seq Data.
    Grandi F; Caroli J; Romano O; Marchionni M; Forcato M; Bicciato S
    J Mol Biol; 2022 Jun; 434(11):167560. PubMed ID: 35662457
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data.
    Hong R; Koga Y; Bandyadka S; Leshchyk A; Wang Y; Akavoor V; Cao X; Sarfraz I; Wang Z; Alabdullatif S; Jansen F; Yajima M; Johnson WE; Campbell JD
    Nat Commun; 2022 Mar; 13(1):1688. PubMed ID: 35354805
    [TBL] [Abstract][Full Text] [Related]  

  • 4. scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets.
    Liu H; Li H; Sharma A; Huang W; Pan D; Gu Y; Lin L; Sun X; Liu H
    Brief Bioinform; 2023 May; 24(3):. PubMed ID: 37183449
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control.
    Osorio D; Cai JJ
    Bioinformatics; 2021 May; 37(7):963-967. PubMed ID: 32840568
    [TBL] [Abstract][Full Text] [Related]  

  • 6. clustifyr: an R package for automated single-cell RNA sequencing cluster classification.
    Fu R; Gillen AE; Sheridan RM; Tian C; Daya M; Hao Y; Hesselberth JR; Riemondy KA
    F1000Res; 2020; 9():223. PubMed ID: 32765839
    [TBL] [Abstract][Full Text] [Related]  

  • 7. scruff: an R/Bioconductor package for preprocessing single-cell RNA-sequencing data.
    Wang Z; Hu J; Johnson WE; Campbell JD
    BMC Bioinformatics; 2019 May; 20(1):222. PubMed ID: 31046658
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A rank-based marker selection method for high throughput scRNA-seq data.
    Vargo AHS; Gilbert AC
    BMC Bioinformatics; 2020 Oct; 21(1):477. PubMed ID: 33097004
    [TBL] [Abstract][Full Text] [Related]  

  • 9. CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny.
    Kong GL; Nguyen TT; Rosales WK; Panikar AD; Cheney JHW; Lusardi TA; Yashar WM; Curtiss BM; Carratt SA; Braun TP; Maxson JE
    BMC Bioinformatics; 2024 Apr; 25(1):142. PubMed ID: 38566005
    [TBL] [Abstract][Full Text] [Related]  

  • 10. ascend: R package for analysis of single-cell RNA-seq data.
    Senabouth A; Lukowski SW; Hernandez JA; Andersen SB; Mei X; Nguyen QH; Powell JE
    Gigascience; 2019 Aug; 8(8):. PubMed ID: 31505654
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Single-cell Mayo Map (scMayoMap): an easy-to-use tool for cell type annotation in single-cell RNA-sequencing data analysis.
    Yang L; Ng YE; Sun H; Li Y; Chini LCS; LeBrasseur NK; Chen J; Zhang X
    BMC Biol; 2023 Oct; 21(1):223. PubMed ID: 37858214
    [TBL] [Abstract][Full Text] [Related]  

  • 12. scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data.
    Ye W; Ji G; Ye P; Long Y; Xiao X; Li S; Su Y; Wu X
    BMC Genomics; 2019 May; 20(1):347. PubMed ID: 31068142
    [TBL] [Abstract][Full Text] [Related]  

  • 13. No detectable alloreactive transcriptional responses under standard sample preparation conditions during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells.
    McGinnis CS; Siegel DA; Xie G; Hartoularos G; Stone M; Ye CJ; Gartner ZJ; Roan NR; Lee SA
    BMC Biol; 2021 Jan; 19(1):10. PubMed ID: 33472616
    [TBL] [Abstract][Full Text] [Related]  

  • 14. V-SVA: an R Shiny application for detecting and annotating hidden sources of variation in single-cell RNA-seq data.
    Lawlor N; Marquez EJ; Lee D; Ucar D
    Bioinformatics; 2020 Jun; 36(11):3582-3584. PubMed ID: 32119082
    [TBL] [Abstract][Full Text] [Related]  

  • 15. WASP: a versatile, web-accessible single cell RNA-Seq processing platform.
    Hoek A; Maibach K; Özmen E; Vazquez-Armendariz AI; Mengel JP; Hain T; Herold S; Goesmann A
    BMC Genomics; 2021 Mar; 22(1):195. PubMed ID: 33736596
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Single-Cell Transcriptomics of Immune Cells: Cell Isolation and cDNA Library Generation for scRNA-Seq.
    Arsenio J
    Methods Mol Biol; 2020; 2184():1-18. PubMed ID: 32808214
    [TBL] [Abstract][Full Text] [Related]  

  • 17. LRT: Integrative analysis of scRNA-seq and scTCR-seq data to investigate clonal differentiation heterogeneity.
    Xie J; Jeon H; Xin G; Ma Q; Chung D
    PLoS Comput Biol; 2023 Jul; 19(7):e1011300. PubMed ID: 37428794
    [TBL] [Abstract][Full Text] [Related]  

  • 18. scMAGS: Marker gene selection from scRNA-seq data for spatial transcriptomics studies.
    Baran Y; Doğan B
    Comput Biol Med; 2023 Mar; 155():106634. PubMed ID: 36774895
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. A statistical simulator scDesign for rational scRNA-seq experimental design.
    Li WV; Li JJ
    Bioinformatics; 2019 Jul; 35(14):i41-i50. PubMed ID: 31510652
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.