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Volumn 29, Issue 5, 2013, Pages 605-613

SIBER: Systematic identification of bimodally expressed genes using RNAseq data

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BREAST TUMOR; CLUSTER ANALYSIS; COMPUTER PROGRAM; DNA MICROARRAY; FEMALE; GENE EXPRESSION PROFILING; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN; METABOLISM; METHODOLOGY; SEQUENCE ANALYSIS;

EID: 84874702931     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/bts713     Document Type: Article
Times cited : (23)

References (28)
  • 2
    • 77958471357 scopus 로고    scopus 로고
    • Differential expression analysis for sequence count data
    • Anders, S. and Huber, W. (2010) Differential expression analysis for sequence count data. Genome Biol., 11, R106.
    • (2010) Genome Biol. , vol.11
    • Anders, S.1    Huber, W.2
  • 3
    • 84865527768 scopus 로고    scopus 로고
    • Detecting differential usage of exons from RNA-Seq data
    • Anders, S. et al. (2012) Detecting differential usage of exons from RNA-Seq data. Genome Res., 22, 2008-2017.
    • (2012) Genome Res. , vol.22 , pp. 2008-2017
    • Anders, S.1
  • 4
    • 0035875668 scopus 로고    scopus 로고
    • Cell signaling can direct either binary or graded transcriptional responses
    • Biggar, S. and Crabtree, H. (2001) Cell signaling can direct either binary or graded transcriptional responses. EMBO J., 20, 3167.
    • (2001) EMBO J. , vol.20 , pp. 3167
    • Biggar, S.1    Crabtree, G.2
  • 6
    • 77949481052 scopus 로고    scopus 로고
    • Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments
    • Bullard, J. et al. (2010) Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics, 11, 94.
    • (2010) BMC Bioinformatics , vol.11 , pp. 94
    • Bullard, J.1
  • 7
    • 11844303478 scopus 로고    scopus 로고
    • Mechanism of transcriptional silencing in yeast
    • DOI 10.1016/j.cell.2004.11.030, PII S0092867404010980
    • Chen, L. and Widom, J. (2005) Mechanism of transcriptional silencing in yeast. Cell, 120, 37-48. (Pubitemid 40094601)
    • (2005) Cell , vol.120 , Issue.1 , pp. 37-48
    • Chen, L.1    Widom, J.2
  • 9
    • 79958117254 scopus 로고    scopus 로고
    • The NBP negative binomial model for assessing differential gene expression from RNA-Seq
    • Di, Y. et al. (2011) The NBP negative binomial model for assessing differential gene expression from RNA-Seq. Stat. Appl. Genet. Mol. Biol., 10, 24.
    • (2011) Stat. Appl. Genet. Mol. Biol. , vol.10 , pp. 24
    • Di, Y.1
  • 10
    • 39849101183 scopus 로고    scopus 로고
    • Switch-like genes populate cell communication pathways and are enriched for extracellular proteins
    • Ertel, A. and Tozeren, A. (2008) Switch-like genes populate cell communication pathways and are enriched for extracellular proteins. BMC Genomics, 9, 3.
    • (2008) BMC Genomics , vol.9 , pp. 3
    • Ertel, A.1    Tozeren, A.2
  • 11
    • 0035998835 scopus 로고    scopus 로고
    • Model-based clustering discriminant analysis, and density estimation
    • Fraley, C. and Raftery, A. (2002) Model-based clustering, discriminant analysis, and density estimation. J. Am. Stat. Assoc., 97, 611-631.
    • (2002) J. Am. Stat. Assoc. , vol.97 , pp. 611-631
    • Fraley, C.1    Raftery, A.2
  • 12
    • 77955298482 scopus 로고    scopus 로고
    • BaySeq: Empirical Bayesian methods for identifying differential expression in sequence count data
    • Hardcastle, T. and Kelly, K. (2010) BaySeq: Empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics, 11, 422.
    • (2010) BMC Bioinformatics , vol.11 , pp. 422
    • Hardcastle, T.1    Kelly, K.2
  • 13
    • 77952534179 scopus 로고    scopus 로고
    • Comparison of scores for bimodality of gene expression distributions and genome-wide evaluation of the prognostic relevance of high-scoring genes
    • Hellwig, B. et al. (2010) Comparison of scores for bimodality of gene expression distributions and genome-wide evaluation of the prognostic relevance of high-scoring genes. BMC Bioinformatics, 11, 276.
    • (2010) BMC Bioinformatics , vol.11 , pp. 276
    • Hellwig, B.1
  • 14
    • 83255185240 scopus 로고    scopus 로고
    • Melanoma antigen family A identified by the bimodality index defines a subset of triple negative breast cancers as candidates for immune response augmentation
    • Karn, T. et al. (2012)Melanoma antigen family A identified by the bimodality index defines a subset of triple negative breast cancers as candidates for immune response augmentation. Eur. J. Cancer., 84, 12-23.
    • (2012) Eur. J. Cancer. , vol.84 , pp. 12-23
    • Karn, T.1
  • 15
    • 84858606519 scopus 로고    scopus 로고
    • A comparison of statistical methods for detecting differentially expressed genes from RNA-seq data
    • Kvam, V. M. et al. (2012) A comparison of statistical methods for detecting differentially expressed genes from RNA-seq data. Am. J. Bot., 99, 248-256.
    • (2012) Am. J. Bot. , vol.99 , pp. 248-256
    • Kvam, V.M.1
  • 16
    • 79551494866 scopus 로고    scopus 로고
    • Accurate quantification of transcriptome from RNA-Seq data by effective length normalization
    • Lee, S. et al. (2011) Accurate quantification of transcriptome from RNA-Seq data by effective length normalization. Nucleic Acids Res., 39, e9.
    • (2011) Nucleic Acids Res. , vol.39
    • Lee, S.1
  • 17
    • 17044444207 scopus 로고    scopus 로고
    • Binary and graded responses in gene networks
    • Louis, M. and Becskei, A. (2002) Binary and graded responses in gene networks. Sci STKE, 2002, pe33.
    • (2002) Sci STKE , vol.2002
    • Louis, M.1    Becskei, A.2
  • 18
    • 50649089207 scopus 로고    scopus 로고
    • RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays
    • Marioni, J. et al. (2008) RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res., 18, 1509-1517.
    • (2008) Genome Res. , vol.18 , pp. 1509-1517
    • Marioni, J.1
  • 19
    • 79957882567 scopus 로고    scopus 로고
    • RNA-seq: Technical variability and sampling
    • McIntyre, L. et al. (2011) RNA-seq: technical variability and sampling. BMC Genomics, 12, 293.
    • (2011) BMC Genomics , vol.12 , pp. 293
    • McIntyre, L.1
  • 20
    • 46249106990 scopus 로고    scopus 로고
    • Mapping and quantifying mammalian transcriptomes by RNA-Seq
    • DOI 10.1038/nmeth.1226, PII NMETH.1226
    • Mortazavi, A. et al. (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods, 5, 621-628. (Pubitemid 351911867)
    • (2008) Nature Methods , vol.5 , Issue.7 , pp. 621-628
    • Mortazavi, A.1    Williams, B.A.2    McCue, K.3    Schaeffer, L.4    Wold, B.5
  • 21
    • 77953176036 scopus 로고    scopus 로고
    • A scaling normalization method for differential expression analysis of RNA-seq data
    • Robinson, M. and Oshlack, A. (2010) A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol., 11, R25.
    • (2010) Genome Biol. , vol.11
    • Robinson, M.1    Oshlack, A.2
  • 22
    • 36448981743 scopus 로고    scopus 로고
    • Moderated statistical tests for assessing differences in tag abundance
    • DOI 10.1093/bioinformatics/btm453
    • Robinson, M. and Smyth, H. (2007) Moderated statistical tests for assessing differences in tag abundance. Bioinformatics, 23, 2881-2887. (Pubitemid 350162894)
    • (2007) Bioinformatics , vol.23 , Issue.21 , pp. 2881-2887
    • Robinson, M.D.1    Smyth, G.K.2
  • 23
    • 75249087100 scopus 로고    scopus 로고
    • EdgeR: A Bioconductor package for differential expression analysis of digital gene expression data
    • Robinson, M. et al. (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26, 139-140.
    • (2010) Bioinformatics , vol.26 , pp. 139-140
    • Robinson, M.1
  • 24
    • 85052549687 scopus 로고    scopus 로고
    • A two-parameter generalized Poisson model to improve the analysis of RNA-seq data
    • Srivastava, S. and Chen, L. (2010) A two-parameter generalized Poisson model to improve the analysis of RNA-seq data. Nucleic Acids Res., 38, e170.
    • (2010) Nucleic Acids Res. , vol.38
    • Srivastava, S.1    Chen, L.2
  • 25
    • 33748708623 scopus 로고    scopus 로고
    • PACK: Profile Analysis using Clustering and Kurtosis to find molecular classifiers in cancer
    • DOI 10.1093/bioinformatics/btl174
    • Teschendorff, A. et al. (2006) PACK: profile analysis using clustering and kurtosis to find molecular classifiers in cancer. Bioinformatics, 22, 2269-2275. (Pubitemid 44390883)
    • (2006) Bioinformatics , vol.22 , Issue.18 , pp. 2269-2275
    • Teschendorff, A.E.1    Naderi, A.2    Barbosa-Morais, N.L.3    Caldas, C.4
  • 26
    • 34648829133 scopus 로고    scopus 로고
    • An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer
    • Teschendorff, A. et al. (2007) An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol., 8, R157.
    • (2007) Genome Biol. , vol.8
    • Teschendorff, A.1
  • 28
    • 77649269338 scopus 로고    scopus 로고
    • The bimodality Index: A criterion for discovering and ranking bimodal signatures from cancer gene expression profiling data
    • Wang, J. et al. (2009) The bimodality Index: a criterion for discovering and ranking bimodal signatures from cancer gene expression profiling data. Cancer Inform., 7, 199-216.
    • (2009) Cancer Inform. , vol.7 , pp. 199-216
    • Wang, J.1


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