Please cite appropriate references when you publish your results.

Sun J, Nishiyama T, Shimizu K, and Kadota K. TCC: an R package for comparing tag count data with robust normalization strategies. BMC Bioinformatics 2013, 14: 219

Kadota K, Nishiyama T, and Shimizu K. A normalization strategy for comparing tag count data. Algorithms Mol Biol. 2012, 7: 5

Robinson MD and Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010, 11: R25

Kadota K, Nakai Y, Shimizu K: A weighted average difference method for detecting differentially expressed genes from microarray data. Algorithms Mol Biol. 2008, 3: 8

Hardcastle TJ and Kelly KA. baySeq: empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics 2010, 11: 422

Kadota K, Nishimura SI, Bono H, Nakamura S, Hayashizaki Y, Okazaki Y, Takahashi K: Detection of genes with tissue-specific expression patterns using Akaike's Information Criterion (AIC) procedure. Physiol Genomics 2003, 12: 251-259

Anders S and Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010, 11(10): R106

McCarthy DJ, Chen Y and Smyth GK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 2012, 40: 4288-4297

Robinson MD, McCarthy DJ, and Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26(1): 139-140

Kadota K, Ye J, Nakai Y, Terada T, Shimizu K: ROKU: a novel method for identification of tissue-specific genes. BMC Bioinformatics 2006, 7: 294

Ueda T. Simple method for the detection of outliers. Japanese J Appl Stat 1996, 25: 17-26

Robinson MD and Smyth GK. Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics 2008, 9: 321-332

Di Y, Schafer DW, Cumbie JS, and Chang JH. The NBP negative binomial model for assessing differential gene expression from RNA-Seq. Stat Appl Genet Mol Biol. 2011, 10: art24

Corresponding BibTeX entries:

  @Article{,
    title = {TCC: an R package for comparing tag count data with robust
      normalization strategies},
    author = {Sun J and Nishiyama T and Shimizu K and Kadota K},
    journal = {BMC Bioinformatics},
    volume = {14},
    pages = {219},
    year = {2013},
  }

  @Article{,
    title = {A normalization strategy for comparing tag count data},
    author = {Kadota K and Nishiyama T and Shimizu K},
    journal = {Algorithms for Molecular Biology},
    volume = {7},
    pages = {5},
    year = {2012},
  }

  @Article{,
    title = {A scaling normalization method for differential expression
      analysis of RNA-seq data},
    author = {Robinson MD and Oshlack A},
    journal = {Genome Biology},
    volume = {11},
    pages = {R25},
    year = {2010},
  }

  @Article{,
    title = {A weighted average difference method for detecting
      differentially expressed genes from microarray data},
    author = {Kadota K and Nakai Y and Shimizu K},
    journal = {Algorithms Mol Biol.},
    volume = {3},
    pages = {8},
    year = {2008},
  }

  @Article{,
    title = {baySeq: empirical Bayesian methods for identifying
      differential expression in sequence count data},
    author = {Hardcastle TJ and Kelly KA},
    journal = {BMC Bioinformatics},
    volume = {11},
    pages = {422},
    year = {2010},
  }

  @Article{,
    title = {Detection of genes with tissue-specific expression
      patterns using Akaike's Information Criterion (AIC) procedure},
    author = {Kadota K and Nishimura SI and Bono H and Nakamura S and
      Hayashizaki Y and Okazaki Y and Takahashi K},
    journal = {Physiol Genomics},
    volume = {12},
    pages = {-8},
    year = {2003},
  }

  @Article{,
    title = {Differential expression analysis for sequence count data},
    author = {Anders S and Huber W},
    journal = {Genome Biology},
    volume = {11(10)},
    pages = {R106},
    year = {2010},
  }

  @Article{,
    title = {Differential expression analysis of multifactor RNA-Seq
      experiments with respect to biological variation},
    author = {McCarthy DJ and Chen Y and Smyth GK},
    journal = {Nucleic Acids Research},
    volume = {40},
    pages = {-9},
    year = {2012},
  }

  @Article{,
    title = {edgeR: a Bioconductor package for differential expression
      analysis of digital gene expression data},
    author = {Robinson MD and McCarthy DJ and Smyth GK},
    journal = {Bioinformatics},
    volume = {26(1)},
    pages = {-1},
    year = {2010},
  }

  @Article{,
    title = {ROKU: a novel method for identification of tissue-specific
      genes},
    author = {Kadota K and Ye J and Nakai Y and Terada T and Shimizu
      K},
    journal = {BMC Bioinformatics},
    volume = {7},
    pages = {294},
    year = {2006},
  }

  @Article{,
    title = {Simple method for the detection of outliers},
    author = {Ueda T},
    journal = {Japanese J Appl Stat},
    volume = {25},
    pages = {-9},
    year = {1996},
  }

  @Article{,
    title = {Small-sample estimation of negative binomial dispersion,
      with applications to SAGE data},
    author = {Robinson MD and Smyth GK},
    journal = {Biostatistics},
    volume = {9},
    pages = {-11},
    year = {2008},
  }

  @Article{,
    title = {The NBP negative binomial model for assessing differential
      gene expression from RNA-Seq},
    author = {Di Y and Schafer DW and Cumbie JS and Chang JH},
    journal = {Stat Appl Genet Mol Biol},
    volume = {26(1)},
    pages = {-1},
    year = {2010},
  }