BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

173 related articles for article (PubMed ID: 26608751)

  • 1. Detecting differentially expressed genes by smoothing effect of gene length on variance estimation.
    Tang J; Wang F
    J Bioinform Comput Biol; 2015 Dec; 13(6):1542004. PubMed ID: 26608751
    [TBL] [Abstract][Full Text] [Related]  

  • 2. GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data.
    Feng J; Meyer CA; Wang Q; Liu JS; Shirley Liu X; Zhang Y
    Bioinformatics; 2012 Nov; 28(21):2782-8. PubMed ID: 22923299
    [TBL] [Abstract][Full Text] [Related]  

  • 3. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data.
    Wang L; Feng Z; Wang X; Wang X; Zhang X
    Bioinformatics; 2010 Jan; 26(1):136-8. PubMed ID: 19855105
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A two-step integrated approach to detect differentially expressed genes in RNA-Seq data.
    Al Mahi N; Begum M
    J Bioinform Comput Biol; 2016 Dec; 14(6):1650034. PubMed ID: 27774870
    [TBL] [Abstract][Full Text] [Related]  

  • 5. LFCseq: a nonparametric approach for differential expression analysis of RNA-seq data.
    Lin B; Zhang LF; Chen X
    BMC Genomics; 2014; 15 Suppl 10(Suppl 10):S7. PubMed ID: 25560842
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Statistical detection of differentially expressed genes based on RNA-seq: from biological to phylogenetic replicates.
    Gu X
    Brief Bioinform; 2016 Mar; 17(2):243-8. PubMed ID: 26108230
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modifying SAMseq to account for asymmetry in the distribution of effect sizes when identifying differentially expressed genes.
    Kotoka E; Orr M
    Stat Appl Genet Mol Biol; 2017 Nov; 16(5-6):291-312. PubMed ID: 29077555
    [TBL] [Abstract][Full Text] [Related]  

  • 8. DegPack: a web package using a non-parametric and information theoretic algorithm to identify differentially expressed genes in multiclass RNA-seq samples.
    An J; Kim K; Chae H; Kim S
    Methods; 2014 Oct; 69(3):306-14. PubMed ID: 24981074
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Joint estimation of isoform expression and isoform-specific read distribution using multisample RNA-Seq data.
    Suo C; Calza S; Salim A; Pawitan Y
    Bioinformatics; 2014 Feb; 30(4):506-13. PubMed ID: 24307704
    [TBL] [Abstract][Full Text] [Related]  

  • 10. BADGE: a novel Bayesian model for accurate abundance quantification and differential analysis of RNA-Seq data.
    Gu J; Wang X; Halakivi-Clarke L; Clarke R; Xuan J
    BMC Bioinformatics; 2014; 15 Suppl 9(Suppl 9):S6. PubMed ID: 25252852
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Differential gene expression analysis using coexpression and RNA-Seq data.
    Yang EW; Girke T; Jiang T
    Bioinformatics; 2013 Sep; 29(17):2153-61. PubMed ID: 23793751
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A fuzzy method for RNA-Seq differential expression analysis in presence of multireads.
    Consiglio A; Mencar C; Grillo G; Marzano F; Caratozzolo MF; Liuni S
    BMC Bioinformatics; 2016 Nov; 17(Suppl 12):345. PubMed ID: 28185579
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Length bias correction for RNA-seq data in gene set analyses.
    Gao L; Fang Z; Zhang K; Zhi D; Cui X
    Bioinformatics; 2011 Mar; 27(5):662-9. PubMed ID: 21252076
    [TBL] [Abstract][Full Text] [Related]  

  • 14. XBSeq2: a fast and accurate quantification of differential expression and differential polyadenylation.
    Liu Y; Wu P; Zhou J; Johnson-Pais TL; Lai Z; Chowdhury WH; Rodriguez R; Chen Y
    BMC Bioinformatics; 2017 Oct; 18(Suppl 11):384. PubMed ID: 28984183
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Improving Gene-Set Enrichment Analysis of RNA-Seq Data with Small Replicates.
    Yoon S; Kim SY; Nam D
    PLoS One; 2016; 11(11):e0165919. PubMed ID: 27829002
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identifying differentially spliced genes from two groups of RNA-seq samples.
    Wang W; Qin Z; Feng Z; Wang X; Zhang X
    Gene; 2013 Apr; 518(1):164-70. PubMed ID: 23228854
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Integration of RNA-Seq data with heterogeneous microarray data for breast cancer profiling.
    Castillo D; Gálvez JM; Herrera LJ; Román BS; Rojas F; Rojas I
    BMC Bioinformatics; 2017 Nov; 18(1):506. PubMed ID: 29157215
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparative evaluation of gene set analysis approaches for RNA-Seq data.
    Rahmatallah Y; Emmert-Streib F; Glazko G
    BMC Bioinformatics; 2014 Dec; 15(1):397. PubMed ID: 25475910
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown.
    Pertea M; Kim D; Pertea GM; Leek JT; Salzberg SL
    Nat Protoc; 2016 Sep; 11(9):1650-67. PubMed ID: 27560171
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Read-Split-Run: an improved bioinformatics pipeline for identification of genome-wide non-canonical spliced regions using RNA-Seq data.
    Bai Y; Kinne J; Donham B; Jiang F; Ding L; Hassler JR; Kaufman RJ
    BMC Genomics; 2016 Aug; 17 Suppl 7(Suppl 7):503. PubMed ID: 27556805
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.