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.