HTqPCR

HTqPCR analyzes quantitative real-time PCR (qPCR) data to load, assess quality, normalize, visualize, and perform statistical testing on cycle threshold (Ct) values across multiple conditions and replicates.

Key Features:

• Data Handling Across Formats: Supports spatially-defined input formats including ABI TaqMan Low Density Arrays, OpenArray (Applied Biosystems), and LightCycler systems (Roche Applied Science).
• Comprehensive Data Processing: Performs data loading, quality assessment, normalization, and visualization for qPCR datasets.
• Statistical Analysis Capabilities: Provides parametric and non-parametric tests to assess significance of Ct value differences between experimental features.
• High-Throughput Compatibility: Scales to process large numbers of qPCR assays for high-throughput experiments and large datasets.
• R and Bioconductor Integration: Implemented in the R environment and integrates with Bioconductor for compatibility with genomics workflows.

Scientific Applications:

• RNA Expression Profiling: Enables analysis and comparison of gene expression levels across samples and conditions using qPCR Ct data.
• Microarray Data Validation: Validates microarray results through targeted qPCR assay quantification.
• Clinical Diagnostics: Supports development and validation of diagnostic qPCR assays via statistical analysis of Ct values.

Methodology:

Implemented in R and integrating with Bioconductor, HTqPCR performs data loading, quality assessment, normalization, visualization, and parametric and non-parametric statistical testing of cycle threshold (Ct) values.