tilingArray

tilingArray analyzes high-density DNA tiling microarray data from platforms such as Affymetrix GeneChips to segment hybridization signals, infer transcript boundaries, and apply probe-specific background correction and scaling for measuring transcript abundance and transcript architecture in eukaryotic genomes.


Key Features:

  • Segmentation of Hybridization Signal: Segments hybridization intensities along genomic coordinates to identify transcript boundaries from tiling microarray probes.
  • Quantitative Comparability Adjustment: Uses a dynamic programming algorithm to compute a globally optimal piecewise-constant expression profile that enables quantitative comparison across probes despite sequence-dependent response differences.
  • Probe-Specific Background Correction and Scaling: Performs probe-specific background correction and scaling using empirical probe response parameters derived from reference hybridizations, eliminating the need for paired mismatch probes.

Scientific Applications:

  • Complete Transcriptome Characterization: Characterizes complete transcriptomes using high-density DNA tiling microarrays to accurately map transcript boundaries in eukaryotic genomes.
  • Transcription Architecture and Dynamics: Supports analysis of transcriptional architecture and dynamical changes by providing adjusted, comparable probe-level expression profiles.

Methodology:

Dynamic programming to fit a globally optimal piecewise-constant expression profile, segmentation of hybridization signal along genomic coordinates, and probe-specific background correction and scaling using empirical probe response parameters from reference hybridizations.

Topics

Collections

Details

License:
Artistic-2.0
Tool Type:
command-line tool, library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
1/17/2017
Last Updated:
12/16/2018

Operations

Data Inputs & Outputs

Publications

Huber W, Toedling J, Steinmetz LM. Transcript mapping with high-density oligonucleotide tiling arrays. Bioinformatics. 2006;22(16):1963-1970. doi:10.1093/bioinformatics/btl289. PMID:16787969.

Documentation

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