NDRindex

NDRindex provides an R package that quantifies the degree of data aggregation to evaluate preprocessing outcomes (normalization and dimensionality reduction) in single-cell RNA sequencing (scRNA-Seq), enabling objective comparison of preprocessing paths to improve clustering and cell-type enrichment analyses.

Key Features:

• Normalization and Dimensionality Reduction Evaluation: Assesses data quality following normalization and dimensionality reduction steps applied to scRNA-Seq data.
• Data Aggregation Degree Calculation: Computes a degree-of-data-aggregation metric that quantifies aggregation prior to clustering.
• Comprehensive Quality Assessment: Compares alternative preprocessing paths to identify strategies that preserve biological signal for downstream clustering and cell-type enrichment.

Scientific Applications:

• Cell-type identification and clustering accuracy: Evaluates how preprocessing choices affect clustering outcomes and cell type enrichment analyses in scRNA-Seq studies.
• Immunology and virology research: Applied in studies requiring precise cell-type resolution, such as immunology and virology investigations.
• COVID-19 single-cell analyses: Used in COVID-19 scRNA-Seq studies to improve preprocessing quality that influences interpretation of immune responses.

Methodology:

Tests various normalization and dimensionality reduction methods across multiple scRNA-Seq datasets, calculates a degree-of-data-aggregation metric, and evaluates preprocessing paths by comparing resulting clustering outcomes.