qcSSMDhomo

qcSSMDhomo implements statistically grounded quality-control criteria for homoscedastic high-throughput screening (HTS) data, addressing limitations of the traditional Z-factor by accounting for sampling error and establishing theoretical threshold criteria.

Key Features:

• Addressing Z-factor limitations: Identifies four specific issues with the traditional Z-factor: violation of the Pythagorean theorem in statistics; lack of adjustment for sampling error in HTS studies; non-existence of expectation for sample-based Z-factors; and absence of a theoretical basis for threshold criteria.
• Homoscedasticity-based QC: Introduces QC criteria under the assumption of homoscedasticity to ensure consistent variability across groups being compared.
• Sampling-error consideration: Incorporates adjustment for sampling error into the quality-control criteria for HTS assays.
• Theoretical threshold derivation: Establishes a theoretical basis for threshold criteria to replace ad hoc thresholds associated with the traditional Z-factor.
• HTS focus: Tailored specifically for quality assessment in high-throughput screening studies.

Scientific Applications:

• HTS assay quality assessment: Provides improved statistical criteria for evaluating assay quality in high-throughput screening experiments.
• CRISPR/Cas9 and siRNA screening: Demonstrated applicability in HTS studies employing CRISPR/Cas9 and siRNA technologies to improve reliability in genetic screens and related research.

Methodology:

Constructs new QC criteria by assuming homoscedasticity, addressing sampling error, and resolving statistical inconsistencies of the Z-factor (including Pythagorean theorem violations and the absence of expectation) to derive theoretical threshold criteria.