ArrayPipe

ArrayPipe performs processing and analysis of microarray data using configurable computational pipelines for normalization, differential expression detection, quality assessment, visualization, and gene-list comparisons.

Key Features:

• Comprehensive data handling: Processes single slides to large collections including replicates and dye-swaps and accepts outputs from quantification software for dual-labelled arrays.
• Customizable analysis pipelines: Unrestricted arrangement of functions stored as action profiles allowing repeated application and automated processing of large datasets.
• Quality assessment and visualization: Implements slide-level quality assessment and multiple data visualization options.
• Normalization and differential expression: Provides methods for data normalization and detection of differentially expressed genes.
• Gene list comparison: Compares and highlights gene lists to identify overlaps and differences between datasets.
• Auto-parallelization: Supports auto-parallelization to enhance processing efficiency on large datasets.
• Output formats: Exports calculated values as tab-delimited lists compatible with downstream analysis programs.

Scientific Applications:

• Gene expression studies: Identifies differentially expressed genes across conditions to support studies of diseases, treatments, and developmental stages.
• Comparative genomics: Enables comparison and highlighting of gene lists to aid comparative genomic analyses, including evolutionary relationships and functional genomics.
• Pathogenomics: Applies to pathogen-related research such as host–pathogen interactions and microbial resistance mechanism studies.

Methodology:

Configurable processing pipelines implemented as action profiles; processing of dual-labelled arrays including replicates and dye-swaps; acceptance of outputs from quantification software for dual-labelled arrays; slide-level quality assessment and visualization; data normalization and differential expression detection; gene-list comparison and highlighting; auto-parallelization for large-scale processing; export of results as tab-delimited lists.