OEFinder

OEFinder identifies ordering effects (OE) in single-cell RNA sequencing (scRNA-seq) datasets by detecting genes whose expression correlates with cell capture positions on the Fluidigm C1 capture plate (plate output IDs), as described by Leng et al.

Key Features:

• Statistical Methodology: Employs a statistical approach to detect and rank genes affected by ordering effects in scRNA-seq data.
• Correlation Analysis: Evaluates correlations between gene expression and cell capture positions (plate output IDs) on the capture plate.
• Ranked OE Genes: Generates a sorted list of genes exhibiting significant ordering effects to enable exclusion or adjustment in downstream analyses.

Scientific Applications:

• Single-cell transcriptomics quality control: Identifies ordering artifacts that can bias gene expression measurements in single-cell studies.
• Fluidigm C1 artifact correction: Detects and reports ordering effects specific to Fluidigm C1 capture plate layouts as reported by Leng et al.

Methodology:

Analyzes scRNA-seq datasets to detect patterns of gene expression correlated with cell capture positions on the plate, statistically evaluates these correlations, and outputs a ranked list of genes exhibiting significant ordering effects.