sights

sights provides normalization, statistical testing, and diagnostic visualization of high-throughput screening (HTS) assay data to correct systematic and spatial biases in microtitre plates and support identification of biologically active compounds.

Key Features:

• Normalization Methods: Implements a range of normalization techniques to adjust raw HTS data for systematic variation.
• Statistical Tests: Performs formal statistical testing to validate the significance of observed effects in HTS assays.
• Diagnostic Graphical Tools: Generates diagnostic plots for data quality assessment and detection of spatial bias within microtitre plates.
• Study Design Handling: Supports complex study designs including replication and randomization strategies.
• Validation via Titration Series: Enables comparisons among normalization methods using titration series experiments.
• Spatial Bias Correction: Applies spatial bias correction methods and evaluates performance when combined with plate randomization.
• Well Placement Strategies: Accounts for compound placement strategies including consistent well locations or random assignment across plates.

Scientific Applications:

• HTS assay analysis: Improves accuracy and reliability of high-throughput screening data interpretation.
• Compound identification: Supports identification of potent biologically active compounds from screening libraries.
• Drug discovery: Assists workflows in drug discovery that require robust hit detection from large-scale screens.
• Genomics and proteomics applications: Applies to large-scale biological experiments in genomics and proteomics that use HTS-style assays.
• Large library screening: Facilitates screening of large compound libraries by addressing systematic and spatial biases.

Methodology:

Uses normalization techniques, formal statistical tests, diagnostic plotting, comparisons among normalization methods in titration series, spatial bias correction, and randomization and replication strategies for study design.