메뉴 건너뛰기




Volumn 9, Issue 12, 2014, Pages

A note on an exon-based strategy to identify differentially expressed genes in RNA-seq experiments

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPUTER PROGRAM; CONTROLLED STUDY; EXON; GENE EXPRESSION; GENE IDENTIFICATION; GENE TECHNOLOGY; GENETIC ASSOCIATION; HUMAN; NONHUMAN; RNA SEQUENCE; STATISTICAL ANALYSIS; TRANSCRIPTOMICS; FEMALE; GENE EXPRESSION PROFILING; GENETICS; MALE; PROCEDURES; SEQUENCE ANALYSIS;

EID: 84919884409     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0115964     Document Type: Article
Times cited : (10)

References (34)
  • 1
    • 79957842166 scopus 로고    scopus 로고
    • Computational methods for transcriptome annotation and quantification using RNA-seq
    • Garber M, Grabherr MG, Guttman M, Trapnell C (2011) Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Methods 8: 469-477.
    • (2011) Nat Methods , vol.8 , pp. 469-477
    • Garber, M.1    Grabherr, M.G.2    Guttman, M.3    Trapnell, C.4
  • 2
    • 50649089207 scopus 로고    scopus 로고
    • RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays
    • Marioni JC, Mason CE, Mane SM, Stephens M, Gilad Y (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.C.1    Mason, C.E.2    Mane, S.M.3    Stephens, M.4    Gilad, Y.5
  • 4
    • 70449711243 scopus 로고    scopus 로고
    • Computation for ChIP-seq and RNA-seq studies
    • Pepke S, Wold B, Mortazavi A (2009) Computation for ChIP-seq and RNA-seq studies. Nature Methods 6: S22-S32.
    • (2009) Nature Methods , vol.6 , pp. S22-S32
    • Pepke, S.1    Wold, B.2    Mortazavi, A.3
  • 5
    • 77958471357 scopus 로고    scopus 로고
    • Differential expression analysis for sequence count data
    • Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biology 11.
    • (2010) Genome Biology , vol.11
    • Anders, S.1    Huber, W.2
  • 6
    • 77955298482 scopus 로고    scopus 로고
    • baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data
    • Hardcastle T, Kelly K (2010) baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data. Bmc Bioinformatics 11.
    • (2010) Bmc Bioinformatics , vol.11
    • Hardcastle, T.1    Kelly, K.2
  • 7
    • 75249087100 scopus 로고    scopus 로고
    • edgeR: A Bioconductor package for differential expression analysis of digital gene expression data
    • Robinson MD, McCarthy DJ, Smyth GK (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.D.1    McCarthy, D.J.2    Smyth, G.K.3
  • 8
    • 80051941094 scopus 로고    scopus 로고
    • Identification of novel transcripts in annotated genomes using RNA-Seq
    • Roberts A, Pimentel H, Trapnell C, Pachter L (2011) Identification of novel transcripts in annotated genomes using RNA-Seq. Bioinformatics 27: 2325-2329.
    • (2011) Bioinformatics , vol.27 , pp. 2325-2329
    • Roberts, A.1    Pimentel, H.2    Trapnell, C.3    Pachter, L.4
  • 9
    • 84886557480 scopus 로고    scopus 로고
    • Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data
    • Epub ahead of print
    • Li J, Tibshirani R (2011) Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data. Stat Methods Med Res [Epub ahead of print] doi: 101177/0962280211428386.
    • (2011) Stat Methods Med Res
    • Li, J.1    Tibshirani, R.2
  • 11
    • 4544341015 scopus 로고    scopus 로고
    • Linear models and empirical bayes methods for assessing differential expression in microarray experiments
    • Smyth GK (2004) Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3: Article3.
    • (2004) Stat Appl Genet Mol Biol , vol.3
    • Smyth, G.K.1
  • 12
    • 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 (2014) voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15: R29.
    • (2014) Genome Biol , vol.15 , pp. R29
    • Law, C.W.1    Chen, Y.2    Shi, W.3    Smyth, G.K.4
  • 13
    • 84883644707 scopus 로고    scopus 로고
    • Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data
    • Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, et al. (2013) Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. Genome Biology 14.
    • (2013) Genome Biology , vol.14
    • Rapaport, F.1    Khanin, R.2    Liang, Y.3    Pirun, M.4    Krek, A.5
  • 14
    • 84928199480 scopus 로고    scopus 로고
    • Comparison of software packages for detecting differential expression in RNA-seq studies
    • Seyednasrollah F, Laiho A, Elo LL (2013) Comparison of software packages for detecting differential expression in RNA-seq studies. Brief Bioinform.
    • (2013) Brief Bioinform
    • Seyednasrollah, F.1    Laiho, A.2    Elo, L.L.3
  • 15
    • 84858606519 scopus 로고    scopus 로고
    • A comparison of statistical methods for detecting differentially expressed genes from RNA-seq data
    • Kvam VM, Liu P, Si Y (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    Liu, P.2    Si, Y.3
  • 16
    • 84874677498 scopus 로고    scopus 로고
    • A comparison of methods for differential expression analysis of RNA-seq data
    • Soneson C, Delorenzi M (2013) A comparison of methods for differential expression analysis of RNA-seq data. BMC Bioinformatics 14: 91.
    • (2013) BMC Bioinformatics , vol.14 , pp. 91
    • Soneson, C.1    Delorenzi, M.2
  • 18
    • 84859436530 scopus 로고    scopus 로고
    • NCBI Reference Sequences (RefSeq): Current status, new features and genome annotation policy
    • Pruitt K, Tatusova T, Brown G, Maglott D (2012) NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy. Nucleic Acids Research 40: D130-D135.
    • (2012) Nucleic Acids Research , vol.40 , pp. D130-D135
    • Pruitt, K.1    Tatusova, T.2    Brown, G.3    Maglott, D.4
  • 19
    • 84865527768 scopus 로고    scopus 로고
    • Detecting differential usage of exons from RNA-seq data
    • Anders S, Reyes A, Huber W (2012) Detecting differential usage of exons from RNA-seq data. Genome Research 22: 2008-2017.
    • (2012) Genome Research , vol.22 , pp. 2008-2017
    • Anders, S.1    Reyes, A.2    Huber, W.3
  • 20
    • 84872198346 scopus 로고    scopus 로고
    • Differential analysis of gene regulation at transcript resolution with RNA-seq
    • Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, et al. (2013) Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotechnol 31: 46-53.
    • (2013) Nat Biotechnol , vol.31 , pp. 46-53
    • Trapnell, C.1    Hendrickson, D.G.2    Sauvageau, M.3    Goff, L.4    Rinn, J.L.5
  • 21
    • 84888234617 scopus 로고    scopus 로고
    • Systematically differentiating functions for alternatively spliced isoforms through integrating RNA-seq data
    • Eksi R, Li HD, Menon R, Wen Y, Omenn GS, et al. (2013) Systematically differentiating functions for alternatively spliced isoforms through integrating RNA-seq data. PLoS Comput Biol 9: e1003314.
    • (2013) PLoS Comput Biol , vol.9 , pp. e1003314
    • Eksi, R.1    Li, H.D.2    Menon, R.3    Wen, Y.4    Omenn, G.S.5
  • 22
    • 84914170768 scopus 로고    scopus 로고
    • Revisiting the identification of canonical splice isoforms through integration of functional genomics and proteomics evidence
    • Li HD, Menon R, Omenn GS, Guan Y (2014) Revisiting the identification of canonical splice isoforms through integration of functional genomics and proteomics evidence. Proteomics.
    • (2014) Proteomics
    • Li, H.D.1    Menon, R.2    Omenn, G.S.3    Guan, Y.4
  • 24
    • 68849121212 scopus 로고    scopus 로고
    • Probe-level estimation improves the detection of differential splicing in Affymetrix exon array studies
    • Laajala E, Aittokallio T, Lahesmaa R, Elo L (2009) Probe-level estimation improves the detection of differential splicing in Affymetrix exon array studies. Genome Biology 10.
    • (2009) Genome Biology , vol.10
    • Laajala, E.1    Aittokallio, T.2    Lahesmaa, R.3    Elo, L.4
  • 25
    • 2342598771 scopus 로고    scopus 로고
    • A high performance test of differential gene expression for oligonucleotide arrays
    • Lemon W, Liyanarachchi S, You M (2003) A high performance test of differential gene expression for oligonucleotide arrays. Genome Biology 4.
    • (2003) Genome Biology , vol.4
    • Lemon, W.1    Liyanarachchi, S.2    You, M.3
  • 26
    • 33748644662 scopus 로고    scopus 로고
    • Probe-level measurement error improves accuracy in detecting differential gene expression
    • Liu X, Milo M, Lawrence N, Rattray M (2006) Probe-level measurement error improves accuracy in detecting differential gene expression. Bioinformatics 22: 2107-2113.
    • (2006) Bioinformatics , vol.22 , pp. 2107-2113
    • Liu, X.1    Milo, M.2    Lawrence, N.3    Rattray, M.4
  • 27
    • 77949481052 scopus 로고    scopus 로고
    • Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments
    • Bullard JH, Purdom E, Hansen KD, Dudoit S (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.H.1    Purdom, E.2    Hansen, K.D.3    Dudoit, S.4
  • 28
    • 33748491517 scopus 로고    scopus 로고
    • The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements
    • Shi L, Reid L, Jones W, Shippy R, Warrington J, et al. (2006) The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nature Biotechnology 24: 1151-1161.
    • (2006) Nature Biotechnology , vol.24 , pp. 1151-1161
    • Shi, L.1    Reid, L.2    Jones, W.3    Shippy, R.4    Warrington, J.5
  • 29
    • 77950460661 scopus 로고    scopus 로고
    • Understanding mechanisms underlying human gene expression variation with RNA sequencing
    • Pickrell JK, Marioni JC, Pai AA, Degner JF, Engelhardt BE, et al. (2010) Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464: 768-772.
    • (2010) Nature , vol.464 , pp. 768-772
    • Pickrell, J.K.1    Marioni, J.C.2    Pai, A.A.3    Degner, J.F.4    Engelhardt, B.E.5
  • 31
    • 77953095629 scopus 로고    scopus 로고
    • Independent filtering increases detection power for high-throughput experiments
    • Bourgon R, Gentleman R, Huber W (2010) Independent filtering increases detection power for high-throughput experiments. Proc Natl Acad Sci U S A 107: 9546-9551.
    • (2010) Proc Natl Acad Sci U S A , vol.107 , pp. 9546-9551
    • Bourgon, R.1    Gentleman, R.2    Huber, W.3
  • 32
    • 15244353967 scopus 로고    scopus 로고
    • X-inactivation profile reveals extensive variability in X-linked gene expression in females
    • Carrel L, Willard H (2005) X-inactivation profile reveals extensive variability in X-linked gene expression in females. Nature 434: 400-404.
    • (2005) Nature , vol.434 , pp. 400-404
    • Carrel, L.1    Willard, H.2
  • 33
    • 38949090440 scopus 로고    scopus 로고
    • Large-scale population study of human cell lines indicates that dosage compensation is virtually complete
    • Johnston C, Lovell F, Leongamornlert D, Stranger B, Dermitzakis E, et al. (2008) Large-scale population study of human cell lines indicates that dosage compensation is virtually complete. Plos Genetics 4.
    • (2008) Plos Genetics , vol.4
    • Johnston, C.1    Lovell, F.2    Leongamornlert, D.3    Stranger, B.4    Dermitzakis, E.5
  • 34
    • 61449172037 scopus 로고    scopus 로고
    • Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
    • Huang D, Sherman B, Lempicki R (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols 4: 44-57.
    • (2009) Nature Protocols , vol.4 , pp. 44-57
    • Huang, D.1    Sherman, B.2    Lempicki, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.