메뉴 건너뛰기




Volumn 30, Issue 18, 2014, Pages 2598-2602

Next maSigPro: Updating maSigPro bioconductor package for RNA-seq time series

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGY; COMPUTER PROGRAM; GENE EXPRESSION PROFILING; METHODOLOGY; SEQUENCE ANALYSIS; STATISTICAL MODEL; TIME;

EID: 84907546454     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btu333     Document Type: Article
Times cited : (236)

References (23)
  • 1
    • 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 , pp. R106
    • Anders, S.1    Huber, W.2
  • 2
    • 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
  • 3
    • 33646147811 scopus 로고    scopus 로고
    • MaSigPro: A method to identify significantly differential expression profiles in time-course microarray experiments
    • Conesa, A. et al. (2006) maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments. Bioinformatics, 22, 1096-1102.
    • (2006) Bioinformatics , vol.22 , pp. 1096-1102
    • Conesa, A.1
  • 5
    • 84878969764 scopus 로고    scopus 로고
    • Mosaic genome structure of the barley powdery mildew pathogen and conservation of transcriptional programs in divergent hosts
    • Hacquard, S. et al. (2013) Mosaic genome structure of the barley powdery mildew pathogen and conservation of transcriptional programs in divergent hosts. Proc. Natl Acad. Sci. USA, 110, 2219-2228.
    • (2013) Proc. Natl Acad. Sci. USA , vol.110 , pp. 2219-2228
    • Hacquard, S.1
  • 6
    • 57249086249 scopus 로고    scopus 로고
    • Transcriptional profiling of mRNA expression in the mouse distal colon
    • Hoogerwerf, W.A. et al. (2008) Transcriptional profiling of mRNA expression in the mouse distal colon. Gastroenterology, 135, 2019-2029.
    • (2008) Gastroenterology , vol.135 , pp. 2019-2029
    • Hoogerwerf, W.A.1
  • 7
    • 37549071528 scopus 로고    scopus 로고
    • Spatial differentiation in the vegetative mycelium of Aspergillus niger
    • Levin, A. et al. (2007) Spatial differentiation in the vegetative mycelium of Aspergillus niger. Eukaryot. Cell, 6, 2311-2322.
    • (2007) Eukaryot. Cell , vol.6 , pp. 2311-2322
    • Levin, A.1
  • 8
    • 84893242996 scopus 로고    scopus 로고
    • RNA-seq differential expression studies: More sequence or more replication?
    • Liu, Y. et al. (2014) RNA-seq differential expression studies: more sequence or more replication? Bioinformatics, 30, 301-304.
    • (2014) Bioinformatics , vol.30 , pp. 301-304
    • Liu, Y.1
  • 9
    • 84870586000 scopus 로고    scopus 로고
    • Conservation of NLR-triggered immunity across plant lineages
    • Maekawa, T. et al. (2012) Conservation of NLR-triggered immunity across plant lineages. Proc. Natl Acad. Sci. USA, 109, 20119-20123.
    • (2012) Proc. Natl Acad. Sci. USA , vol.109 , pp. 20119-20123
    • Maekawa, T.1
  • 11
    • 77954339096 scopus 로고    scopus 로고
    • Babelomics: An integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling
    • Medina, I. et al. (2010) Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling. Nucleic Acids Res., 38, W210-W213.
    • (2010) Nucleic Acids Res. , vol.38 , pp. W210-W213
    • Medina, I.1
  • 12
    • 46249106990 scopus 로고    scopus 로고
    • Mapping and quantifying mammalian transcriptomes by RNA-Seq
    • Mortazavi, A. et al. (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods, 5, 621-628.
    • (2008) Nat. Methods , vol.5 , pp. 621-628
    • Mortazavi, A.1
  • 13
    • 67649100479 scopus 로고    scopus 로고
    • Functional assessment of time course microarray data
    • Nueda, MJ. et al. (2009) Functional assessment of time course microarray data. BMC Bioinformatics, 10 (Suppl. 6), S9.
    • (2009) BMC Bioinformatics , vol.10 , pp. S9
    • Nueda, M.J.1
  • 14
    • 77954273698 scopus 로고    scopus 로고
    • Serial Expression Analysis: A web tool for the analysis of serial gene expression data
    • Nueda, MJ. et al. (2010) Serial Expression Analysis: a web tool for the analysis of serial gene expression data. Nucleic Acids Res., 3822, 239-245.
    • (2010) Nucleic Acids Res. , vol.3822 , pp. 239-245
    • Nueda, M.J.1
  • 15
    • 84863569198 scopus 로고    scopus 로고
    • ARSyN: A method for the identification and removal of systematic noise in multifactorial time course microarray experiments
    • Nueda, MJ. et al. (2012) ARSyN: a method for the identification and removal of systematic noise in multifactorial time course microarray experiments. Biostatistics, 13, 553-566.
    • (2012) Biostatistics , vol.13 , pp. 553-566
    • Nueda, M.J.1
  • 16
    • 83455238345 scopus 로고    scopus 로고
    • GC-content normalization for RNA-Seq data
    • Risso, D. et al. (2011) GC-content normalization for RNA-Seq data. BMC Bioinformatics, 12, 480.
    • (2011) BMC Bioinformatics , vol.12 , pp. 480
    • Risso, D.1
  • 17
    • 84871946825 scopus 로고    scopus 로고
    • Streaming fragment assignment for real-time analysis of sequencing experiments
    • Roberts, A. and Pachter, L. (2013) Streaming fragment assignment for real-time analysis of sequencing experiments. Nat. Methods, 10, 71-73.
    • (2013) Nat. Methods , vol.10 , pp. 71-73
    • Roberts, A.1    Pachter, L.2
  • 18
    • 77953176036 scopus 로고    scopus 로고
    • A scaling normalization method for differential expression analysis of RNA-Seq data
    • Robinson, M.D. 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 , pp. R25
    • Robinson, M.D.1    Oshlack, A.2
  • 19
    • 75249087100 scopus 로고    scopus 로고
    • EdgeR: A Bioconductor package for differential expression analysis
    • Robinson, M.D. et al. (2010) edgeR: a Bioconductor package for differential expression analysis. Bioinformatics, 26, 139-140.
    • (2010) Bioinformatics , vol.26 , pp. 139-140
    • Robinson, M.D.1
  • 20
    • 84892728434 scopus 로고    scopus 로고
    • Sequencing depth and coverage: Key considerations in genomic analyses
    • Sims, D. et al. (2014) Sequencing depth and coverage: key considerations in genomic analyses. Nat. Rev. Genet., 15, 121-132.
    • (2014) Nat. Rev. Genet. , vol.15 , pp. 121-132
    • Sims, D.1
  • 21
    • 83055192078 scopus 로고    scopus 로고
    • Differential expression in RNAseq: A matter of depth
    • Tarazona, S. et al. (2011) Differential expression in RNAseq: a matter of depth. Genome Res., 21, 2213-2223.
    • (2011) Genome Res. , vol.21 , pp. 2213-2223
    • Tarazona, S.1
  • 22
    • 84859885816 scopus 로고    scopus 로고
    • Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks
    • Trapnell, C. et al. (2012) Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc, 7, 562-578.
    • (2012) Nat. Protoc , vol.7 , pp. 562-578
    • Trapnell, C.1
  • 23
    • 33847335001 scopus 로고    scopus 로고
    • Analysis of 13000 unique Citrus clusters associated with fruit quality, production and salinity tolerance
    • Terol, J. et al. (2007) Analysis of 13000 unique Citrus clusters associated with fruit quality, production and salinity tolerance. BMC Genomics, 8, 31.
    • (2007) BMC Genomics , vol.8 , pp. 31
    • Terol, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.