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twilight

twilight is an R/Bioconductor package that includes several functions for the statistical analysis of two-condition microarray data. The main algorithm for estimating the local false discovery rate is described in Scheid and Spang (2004a, 2004b). The newer versions of twilight include the permutation filtering algorithm introduced in Scheid and Spang (2006, 2007). For further information please visit the compdiag projects Local False Discovery Rate or Permutation Filtering.

Download

Package twilight runs under Linux, Windows, and Mac OS. Please download the current package from Bioconductor. To run the package, you will need R. Package twilight includes a user's manual which can be downloaded separately from the link above.

Literature

• Scheid S and Spang R (2007):
  Compensating for unknown confounders in microarray data analysis using filtered permutations
  Journal of Computational Biology 14(5):669-681.
• Scheid S and Spang R (2006):
  Permutation filtering: A novel concept for significance analysis of large-scale genomic data
  In: Apostolico A, Guerra C, Istrail S, Pevzner P, and Waterman M (Eds.): Research in Computational Molecular Biology: 10th Annual International Conference, Proceedings of RECOMB 2006, Venice, Italy, April 2-5, 2006.
  Lecture Notes in Computer Science vol. 3909, Springer, Heidelberg, pp. 338-347.
  ISSN: 0302-9743, ISBN: 3-540-33295-2.
• Scheid S and Spang R (2005):
  twilight; a Bioconductor package for estimating the local false discovery rate
  Bioinformatics 21(12):2921-2922.
• Scheid S and Spang R (2004a):
  A stochastic downhill search algorithm for estimating the local false discovery rate
  IEEE Transactions on Computational Biology and Bioinformatics 1(3):98-108.
• Scheid S and Spang R (2004b):
  Estimation of Local False Discovery Rates - User's Guide to the Bioconductor Package TWILIGHT
  CompDiag Technical Report Nr. 2004/01.

download literature

Non-academic users

For commercial use of TWILIGHT, please visit the webpage of the NGFN Technology Transfer Center on genome-marketplace. [ pdf ]

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