SeqGate

SeqGate rationalizes the filtering of lowly expressed features by analyzing the distribution of counts in replicate samples to establish a data-driven threshold above which sequenced features can be considered confidently quantified.

Key Features:

• Replicate-based count distribution analysis: SeqGate analyzes the distribution of counts across replicate samples rather than relying on arbitrary thresholds.
• Confidence-based threshold determination: The method establishes a gate threshold above which sequenced features are considered as confidently quantified.

Scientific Applications:

• Pre-statistical filtering of RNA-seq data: SeqGate provides a rationalized approach to filtering lowly expressed genes or other sequenced features before downstream statistical analysis.

Methodology:

SeqGate analyzes the distribution of counts in replicate samples to determine a threshold for confident quantification of sequenced features.