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Tilescope: online analysis pipeline for high-density tiling microarray data.

Zhengdong D Zhang1, Joel Rozowsky, Hugo Y K Lam

  • 1Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA. zhengdong.zhang@yale.edu

Genome Biology
|May 16, 2007
PubMed
Summary
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We created Tilescope, an automated pipeline for analyzing high-density tiling-array data. This tool normalizes signals, combines experiments, and identifies genomic features, offering a user-friendly interface for data analysis.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-density tiling-array data analysis requires sophisticated computational tools.
  • Existing methods may lack full integration or user-friendliness.

Purpose of the Study:

  • To develop an automated, integrated data processing pipeline for high-density tiling-array data.
  • To provide a user-friendly interface for efficient genomic feature identification.

Main Methods:

  • Developed Tilescope, a modular, three-tiered data processing pipeline.
  • Implemented automated signal normalization, replicate combination, and element scoring.
  • Integrated a graphical user interface for results presentation.

Main Results:

Related Experiment Videos

  • Tilescope fully automates the analysis of high-density tiling-array data.
  • The pipeline successfully normalizes signals, combines experiments, and identifies genomic features.
  • Results are presented in an organized, downloadable web page.

Conclusions:

  • Tilescope offers a comprehensive and user-friendly solution for high-density tiling-array data analysis.
  • The pipeline's modular architecture supports parallelism and facilitates further research.