메뉴 건너뛰기




Volumn 9, Issue , 2015, Pages 11-19

B-cell and monocyte contribution to systemic lupus erythematosus identified by cell-type-specific differential expression analysis in RNA-seq data

Author keywords

Cell type specific; CsSAM; Deconvolution; DSection; RNA seq; SLE

Indexed keywords

IMMUNOGLOBULIN; RNA;

EID: 84946922626     PISSN: None     EISSN: 11779322     Source Type: Journal    
DOI: 10.4137/BBI.S29470     Document Type: Article
Times cited : (9)

References (55)
  • 1
    • 84875461762 scopus 로고    scopus 로고
    • Mechanisms of disease for the clinician: Systemic lupus erythematosus
    • Frieri M. Mechanisms of disease for the clinician: systemic lupus erythematosus. Ann Allergy Asthma Immunol. 2013;110(4):228-32.
    • (2013) Ann Allergy Asthma Immunol , vol.110 , Issue.4 , pp. 228-232
    • Frieri, M.1
  • 2
    • 58149214308 scopus 로고    scopus 로고
    • Altered B cell receptor signaling in human systemic lupus erythematosus
    • Jenks SA, Sanz I. Altered B cell receptor signaling in human systemic lupus erythematosus. Autoimmun Rev. 2009;8(3):209-13.
    • (2009) Autoimmun Rev , vol.8 , Issue.3 , pp. 209-213
    • Jenks, S.A.1    Sanz, I.2
  • 3
    • 67749112023 scopus 로고    scopus 로고
    • Deconvolution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus
    • Abbas AR, Wolslegel K, Seshasayee D, Modrusan Z, Clark HF. Deconvolution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus. PLoS One. 2009;4(7):e6098.
    • (2009) PLoS One , vol.4 , Issue.7
    • Abbas, A.R.1    Wolslegel, K.2    Seshasayee, D.3    Modrusan, Z.4    Clark, H.F.5
  • 5
    • 84937560192 scopus 로고    scopus 로고
    • Comparison of RNA-seq and microarray-based models for clinical endpoint prediction
    • Zhang W, Yu Y, Hertwig F, et al. Comparison of RNA-seq and microarray-based models for clinical endpoint prediction. Genome Biol. 2015;16(1):133.
    • (2015) Genome Biol , vol.16 , Issue.1 , pp. 133
    • Zhang, W.1    Yu, Y.2    Hertwig, F.3
  • 6
    • 84884700345 scopus 로고    scopus 로고
    • Gene expression and regulation in systemic lupus erythematosus
    • Frangou EA, Bertsias GK, Boumpas DT. Gene expression and regulation in systemic lupus erythematosus. Eur J Clin Invest. 2013;43(10):1084-96.
    • (2013) Eur J Clin Invest , vol.43 , Issue.10 , pp. 1084-1096
    • Frangou, E.A.1    Bertsias, G.K.2    Boumpas, D.T.3
  • 7
    • 77951634577 scopus 로고    scopus 로고
    • Cell type-specific gene expression differences in complex tissues
    • Shen-Orr SS, Tibshirani R, Khatri P, et al. Cell type-specific gene expression differences in complex tissues. Nat Methods. 2010;7(4):287-9.
    • (2010) Nat Methods , vol.7 , Issue.4 , pp. 287-289
    • Shen-Orr, S.S.1    Tibshirani, R.2    Khatri, P.3
  • 8
    • 84882727548 scopus 로고    scopus 로고
    • CellMix: A comprehensive toolbox for gene expression deconvolution
    • Gaujoux R, Seoighe C. CellMix: a comprehensive toolbox for gene expression deconvolution. Bioinformatics. 2013;29(17):2211-2.
    • (2013) Bioinformatics , vol.29 , Issue.17 , pp. 2211-2212
    • Gaujoux, R.1    Seoighe, C.2
  • 10
    • 0035224389 scopus 로고    scopus 로고
    • Separation of samples into their constituents using gene expression data
    • Venet D, Pecasse F, Maenhaut C, Bersini H. Separation of samples into their constituents using gene expression data. Bioinformatics. 2001;17(suppl 1):S279-87.
    • (2001) Bioinformatics , vol.17 , pp. S279-S287
    • Venet, D.1    Pecasse, F.2    Maenhaut, C.3    Bersini, H.4
  • 11
    • 84928927858 scopus 로고    scopus 로고
    • Robust enumeration of cell subsets from tissue expression profiles
    • Newman AM, Liu CL, Green MR, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453-7.
    • (2015) Nat Methods , vol.12 , Issue.5 , pp. 453-457
    • Newman, A.M.1    Liu, C.L.2    Green, M.R.3
  • 12
    • 0035942271 scopus 로고    scopus 로고
    • Significance analysis of microarrays applied to the ionizing radiation response
    • Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A. 2001;98(9):5116-21.
    • (2001) Proc Natl Acad Sci U S A , vol.98 , Issue.9 , pp. 5116-5121
    • Tusher, V.G.1    Tibshirani, R.2    Chu, G.3
  • 13
    • 84924629414 scopus 로고    scopus 로고
    • Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
    • Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.
    • (2014) Genome Biol , vol.15 , Issue.12 , pp. 550
    • Love, M.I.1    Huber, W.2    Anders, S.3
  • 14
    • 75249087100 scopus 로고    scopus 로고
    • edgeR: A bioconductor package for differential expression analysis of digital gene expression data
    • Robinson MD, McCarthy DJ, Smyth GK. edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26(1):139-40.
    • (2010) Bioinformatics , vol.26 , Issue.1 , pp. 139-140
    • Robinson, M.D.1    McCarthy, D.J.2    Smyth, G.K.3
  • 16
    • 4544341015 scopus 로고    scopus 로고
    • Linear models and empirical Bayes methods for assessing differential expression in microarray experiments
    • Smyth GK. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004;3:Article 3.
    • (2004) Stat Appl Genet Mol Biol , vol.3
    • Smyth, G.K.1
  • 17
    • 77958471357 scopus 로고    scopus 로고
    • Differential expression analysis for sequence count data
    • Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11(10):R106.
    • (2010) Genome Biol , vol.11 , Issue.10
    • Anders, S.1    Huber, W.2
  • 18
    • 84983732319 scopus 로고    scopus 로고
    • Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package
    • pii:gkv711
    • Tarazona S, Furió-Tarí P, Turrà D, et al. Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package. Nucleic Acids Res. 2015. pii:gkv711.
    • (2015) Nucleic Acids Res
    • Tarazona, S.1    Furió-Tarí, P.2    Turrà, D.3
  • 19
    • 84905049901 scopus 로고    scopus 로고
    • Trimmomatic: A flexible trimmer for Illumina Sequence Data
    • (30(15))
    • Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina Sequence Data. Bioinformatics. 2014. 1(30(15)):p. 2114-20.
    • (2014) Bioinformatics , vol.1 , pp. 2114-2120
    • Bolger, A.M.1    Lohse, M.2    Usadel, B.3
  • 20
    • 84859885816 scopus 로고    scopus 로고
    • Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and cufflinks
    • Trapnell C, Roberts A, Goff L, et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and cufflinks. Nat Protoc. 2012;7(3):562-78.
    • (2012) Nat Protoc , vol.7 , Issue.3 , pp. 562-578
    • Trapnell, C.1    Roberts, A.2    Goff, L.3
  • 21
    • 84928987900 scopus 로고    scopus 로고
    • HTSeq-a Python framework to work with high-throughput sequencing data
    • Anders S, Pyl PT, Huber W. HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics. 2014;15(31(2)): p.166-9.
    • (2014) Bioinformatics , vol.15 , Issue.2-31 , pp. 166-169
    • Anders, S.1    Pyl, P.T.2    Huber, W.3
  • 22
    • 84905912949 scopus 로고    scopus 로고
    • A comparative study of techniques for differential expression analysis on RNA-Seq data
    • Zhang ZH, Jhaveri DJ, Marshall VM, et al. A comparative study of techniques for differential expression analysis on RNA-Seq data. PLoS One. 2014;9(8):e103207.
    • (2014) PLoS One , vol.9 , Issue.8
    • Zhang, Z.H.1    Jhaveri, D.J.2    Marshall, V.M.3
  • 23
    • 84874677498 scopus 로고    scopus 로고
    • A comparison of methods for differential expression analysis of RNA-seq data
    • Soneson C, Delorenzi M. A comparison of methods for differential expression analysis of RNA-seq data. BMC Bioinformatics. 2013;14:91.
    • (2013) BMC Bioinformatics , vol.14 , pp. 91
    • Soneson, C.1    Delorenzi, M.2
  • 24
    • 84928199480 scopus 로고    scopus 로고
    • Comparison of software packages for detecting differential expression in RNA-seq studies
    • Seyednasrollah F, Laiho A, Elo LL. Comparison of software packages for detecting differential expression in RNA-seq studies. Brief Bioinform. 2015;16(1):59-70.
    • (2015) Brief Bioinform , vol.16 , Issue.1 , pp. 59-70
    • Seyednasrollah, F.1    Laiho, A.2    Elo, L.L.3
  • 25
    • 84883644707 scopus 로고    scopus 로고
    • Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data
    • Rapaport F, Khanin R, Liang Y, et al. Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. Genome Biol. 2013;14(9):R95.
    • (2013) Genome Biol , vol.14 , Issue.9
    • Rapaport, F.1    Khanin, R.2    Liang, Y.3
  • 26
    • 77953176036 scopus 로고    scopus 로고
    • A scaling normalization method for differential expression analysis of RNA-seq data
    • Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010;11(3):R25.
    • (2010) Genome Biol , vol.11 , Issue.3
    • Robinson, M.D.1    Oshlack, A.2
  • 27
    • 84896735766 scopus 로고    scopus 로고
    • Voom: Precision weights unlock linear model analysis tools for RNA-seq read counts
    • Law CW, Chen Y, Shi W, Smyth GK. Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 2014;15(2):R29.
    • (2014) Genome Biol , vol.15 , Issue.2
    • Law, C.W.1    Chen, Y.2    Shi, W.3    Smyth, G.K.4
  • 30
    • 77952123055 scopus 로고    scopus 로고
    • Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation
    • Trapnell C, Williams BA, Pertea G, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28(5):511-5.
    • (2010) Nat Biotechnol , vol.28 , Issue.5 , pp. 511-515
    • Trapnell, C.1    Williams, B.A.2    Pertea, G.3
  • 31
    • 0001677717 scopus 로고
    • Controlling the false discovery rate: A practical and powerful approach to multiple testing
    • Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol. 1995;57(1):289-300.
    • (1995) J R Stat Soc Series B Stat Methodol , vol.57 , Issue.1 , pp. 289-300
    • Benjamini, Y.1    Hochberg, Y.2
  • 32
    • 0035992248 scopus 로고    scopus 로고
    • Empirical Bayes methods and false discovery rates for microarrays
    • Efron B, Tibshirani R. Empirical Bayes methods and false discovery rates for microarrays. Genet Epidemiol. 2002;23(1):70-86.
    • (2002) Genet Epidemiol , vol.23 , Issue.1 , pp. 70-86
    • Efron, B.1    Tibshirani, R.2
  • 33
    • 0036020892 scopus 로고    scopus 로고
    • A direct approach to false discovery rates
    • Storey JD. A direct approach to false discovery rates. J R Stat Soc Series B Stat Methodol. 2002;64(3):479-98.
    • (2002) J R Stat Soc Series B Stat Methodol , vol.64 , Issue.3 , pp. 479-498
    • Storey, J.D.1
  • 34
    • 77958561176 scopus 로고    scopus 로고
    • A comprehensive and universal method for assessing the performance of differential gene expression analyses
    • Dozmorov MG, Guthridge JM, Hurst RE, Dozmorov IM. A comprehensive and universal method for assessing the performance of differential gene expression analyses. PLoS One. 2010;5(9):e12657.
    • (2010) PLoS One , vol.5 , Issue.9
    • Dozmorov, M.G.1    Guthridge, J.M.2    Hurst, R.E.3    Dozmorov, I.M.4
  • 35
    • 67849130563 scopus 로고    scopus 로고
    • ToppGene suite for gene list enrichment analysis and candidate gene prioritization
    • Chen J, Bardes EE, Aronow BJ, Jegga AG. ToppGene suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res. 2009;37(Web Server issue):W305-11.
    • (2009) Nucleic Acids Res , vol.37 , Issue.WEB SERVER ISSUE , pp. W305-W311
    • Chen, J.1    Bardes, E.E.2    Aronow, B.J.3    Jegga, A.G.4
  • 36
    • 28744458859 scopus 로고    scopus 로고
    • Bioconductor: Open software development for computational biology and bioinformatics
    • Gentleman RC, Carey VJ, Bates DM, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5(10):R80.
    • (2004) Genome Biol , vol.5 , Issue.10
    • Gentleman, R.C.1    Carey, V.J.2    Bates, D.M.3
  • 38
    • 0014848980 scopus 로고
    • Antibodies to ribosomal ribonucleic acid (rRNA) in patients with systemic lupus erythematosus (SLE)
    • Lamon EW, Bennett JC. Antibodies to ribosomal ribonucleic acid (rRNA) in patients with systemic lupus erythematosus (SLE). Immunology. 1970;19(3):439-42.
    • (1970) Immunology , vol.19 , Issue.3 , pp. 439-442
    • Lamon, E.W.1    Bennett, J.C.2
  • 39
    • 75649151209 scopus 로고    scopus 로고
    • Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus
    • Javierre BM, Fernandez AF, Richter J, et al. Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus. Genome Res. 2010;20(2):170-9.
    • (2010) Genome Res , vol.20 , Issue.2 , pp. 170-179
    • Javierre, B.M.1    Fernandez, A.F.2    Richter, J.3
  • 40
    • 84891418230 scopus 로고    scopus 로고
    • Circulating levels of soluble MER in lupus reflect M2c activation of monocytes/macrophages, autoantibody specificities and disease activity
    • Zizzo G, Guerrieri J, Dittman LM, Merrill JT, Cohen PL. Circulating levels of soluble MER in lupus reflect M2c activation of monocytes/macrophages, autoantibody specificities and disease activity. Arthritis Res Ther. 2013;15(6):R212.
    • (2013) Arthritis Res Ther , vol.15 , Issue.6
    • Zizzo, G.1    Guerrieri, J.2    Dittman, L.M.3    Merrill, J.T.4    Cohen, P.L.5
  • 41
    • 84907682121 scopus 로고    scopus 로고
    • Association of functional polymorphisms in interferon regulatory factor 2 (IRF2) with susceptibility to systemic lupus erythematosus: A case-control association study
    • Kawasaki A, Furukawa H, Nishida N, et al. Association of functional polymorphisms in interferon regulatory factor 2 (IRF2) with susceptibility to systemic lupus erythematosus: a case-control association study. PLoS One. 2014;9(10):e109764.
    • (2014) PLoS One , vol.9 , Issue.10
    • Kawasaki, A.1    Furukawa, H.2    Nishida, N.3
  • 42
    • 84859924136 scopus 로고    scopus 로고
    • A whole genome methylation analysis of systemic lupus erythematosus: Hypomethylation of the IL10 and IL1R2 promoters is associated with disease activity
    • Lin SY, Hsieh SC, Lin YC, et al. A whole genome methylation analysis of systemic lupus erythematosus: hypomethylation of the IL10 and IL1R2 promoters is associated with disease activity. Genes Immun. 2012;13(3):214-20.
    • (2012) Genes Immun , vol.13 , Issue.3 , pp. 214-220
    • Lin, S.Y.1    Hsieh, S.C.2    Lin, Y.C.3
  • 43
    • 33745034931 scopus 로고    scopus 로고
    • Functional assay of type I interferon in systemic lupus erythematosus plasma and association with anti-RNA binding protein autoantibodies
    • Hua J, Kirou K, Lee C, Crow MK. Functional assay of type I interferon in systemic lupus erythematosus plasma and association with anti-RNA binding protein autoantibodies. Arthritis Rheum. 2006;54(6):1906-16.
    • (2006) Arthritis Rheum , vol.54 , Issue.6 , pp. 1906-1916
    • Hua, J.1    Kirou, K.2    Lee, C.3    Crow, M.K.4
  • 44
    • 62549128139 scopus 로고    scopus 로고
    • A census of human transcription factors: Function, expression and evolution
    • Vaquerizas JM, Kummerfeld SK, Teichmann SA, Luscombe NM. A census of human transcription factors: function, expression and evolution. Nat Rev Genet. 2009;10(4):252-63.
    • (2009) Nat Rev Genet , vol.10 , Issue.4 , pp. 252-263
    • Vaquerizas, J.M.1    Kummerfeld, S.K.2    Teichmann, S.A.3    Luscombe, N.M.4
  • 46
    • 84930379392 scopus 로고    scopus 로고
    • Epigenome profiling reveals significant DNA demethylation of interferon signature genes in lupus neutrophils
    • Coit P, Yalavarthi S, Ognenovski M, et al. Epigenome profiling reveals significant DNA demethylation of interferon signature genes in lupus neutrophils. J Autoimmun. 2015;58:59-66.
    • (2015) J Autoimmun , vol.58 , pp. 59-66
    • Coit, P.1    Yalavarthi, S.2    Ognenovski, M.3
  • 47
    • 79961123152 scopus 로고    scopus 로고
    • RSEM: Accurate transcript quantification from RNA-Seq data with or without a reference genome
    • Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323.
    • (2011) BMC Bioinformatics , vol.12 , pp. 323
    • Li, B.1    Dewey, C.N.2
  • 48
    • 84872033704 scopus 로고    scopus 로고
    • Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples
    • Wagner GP, Kin K, Lynch VJ. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory Biosci. 2012;131(4):281-5.
    • (2012) Theory Biosci , vol.131 , Issue.4 , pp. 281-285
    • Wagner, G.P.1    Kin, K.2    Lynch, V.J.3
  • 49
    • 84887791432 scopus 로고    scopus 로고
    • A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis
    • Dillies MA, Rau A, Aubert J, et al; French StatOmique Consortium. A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Brief Bioinform. 2013;14(6):671-83.
    • (2013) Brief Bioinform , vol.14 , Issue.6 , pp. 671-683
    • Dillies, M.A.1    Rau, A.2    Aubert, J.3
  • 50
    • 84907500627 scopus 로고    scopus 로고
    • RNA-Seq gene profiling-a systematic empirical comparison
    • Fonseca NA, Marioni J, Brazma A. RNA-Seq gene profiling-a systematic empirical comparison. PLoS One. 2014;9(9):e107026.
    • (2014) PLoS One , vol.9 , Issue.9
    • Fonseca, N.A.1    Marioni, J.2    Brazma, A.3
  • 51
    • 0036898577 scopus 로고    scopus 로고
    • Microarray data normalization and transformation
    • Quackenbush J. Microarray data normalization and transformation. Nat Genet. 2002;32(suppl):496-501.
    • (2002) Nat Genet , vol.32 , pp. 496-501
    • Quackenbush, J.1
  • 52
    • 84875700729 scopus 로고    scopus 로고
    • A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression
    • Guintivano J, Aryee MJ, Kaminsky ZA. A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression. Epigenetics. 2013;8(3):290-302.
    • (2013) Epigenetics , vol.8 , Issue.3 , pp. 290-302
    • Guintivano, J.1    Aryee, M.J.2    Kaminsky, Z.A.3
  • 53
    • 84860637797 scopus 로고    scopus 로고
    • DNA methylation arrays as surrogate measures of cell mixture distribution
    • Houseman EA, Accomando WP, Koestler DC, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012;13:86.
    • (2012) BMC Bioinformatics , vol.13 , pp. 86
    • Houseman, E.A.1    Accomando, W.P.2    Koestler, D.C.3
  • 54
    • 84893192328 scopus 로고    scopus 로고
    • Accounting for cellular heterogeneity is critical in epigenome-wide association studies
    • Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 2014;15(2):R31.
    • (2014) Genome Biol , vol.15 , Issue.2
    • Jaffe, A.E.1    Irizarry, R.A.2
  • 55
    • 84883194790 scopus 로고    scopus 로고
    • Measuring cell-type specific differential methylation in human brain tissue
    • Montaño CM, Irizarry RA, Kaufmann WE, et al. Measuring cell-type specific differential methylation in human brain tissue. Genome Biol. 2013;14(8):R94.
    • (2013) Genome Biol , vol.14 , Issue.8
    • Montaño, C.M.1    Irizarry, R.A.2    Kaufmann, W.E.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.