oneChannelGUI

oneChannelGUI provides comprehensive analysis of single-channel microarray data using Bioconductor libraries, with emphasis on Affymetrix 3' expression (IVT) arrays and whole-transcript Gene/Exon 1.0 ST arrays.


Key Features:

  • Bioconductor integration: Add-on package that extends affylmGUI and integrates existing Bioconductor libraries for microarray analysis.
  • Single-channel array support: Supports Affymetrix 3' expression (IVT) arrays and whole-transcript Gene/Exon 1.0 ST arrays.
  • Quality control: Implements rigorous quality assessment protocols for microarray data integrity.
  • Normalization: Provides various normalization techniques to adjust for systematic biases.
  • Filtering: Enables removal of low-quality or irrelevant probes/probesets to improve downstream analyses.
  • Statistical validation: Includes robust statistical methods for assessing significance of results.
  • Data mining: Facilitates extraction of meaningful patterns and insights from large datasets.
  • miRNA/mRNA-seq support: Supports analysis workflows that include miRNA and mRNA-seq data.

Scientific Applications:

  • Gene expression profiling: Generation and analysis of gene-level expression results from single-channel arrays.
  • Exon-level analysis: Analysis of exon-level expression using whole-transcript Gene/Exon 1.0 ST arrays.
  • miRNA and mRNA sequencing analysis: Integration of miRNA/mRNA-seq data analyses alongside microarray data.

Methodology:

Integration of existing Bioconductor tools by extending affylmGUI to provide end-to-end processing steps from quality control through normalization, filtering, statistical validation, and data mining.

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:
11/25/2024

Operations

Publications

Sanges R, Cordero F, Calogero RA. oneChannelGUI: a graphical interface to Bioconductor tools, designed for life scientists who are not familiar with R language. Bioinformatics. 2007;23(24):3406-3408. doi:10.1093/bioinformatics/btm469. PMID:17875544.

Documentation

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