iSAFE

iSAFE identifies specific mutations favored by positive selection within large genomic regions (~5 Mbp) using population genetics signals without requiring demographic history, phenotypic data, or functional annotations.

Key Features:

• Statistical Approach: Uses a novel statistic derived solely from population genetics signals to pinpoint the mutation favored within a selective sweep.
• Independence from External Data: Operates without requiring demographic history, phenotypic characteristics, or functional annotations.
• Large Region Analysis: Analyzes extensive genomic regions (~5 Mbp) to localize favored alleles across broad genomic intervals.

Scientific Applications:

• Evolutionary biology: Localizes mutations under positive selection to study adaptive processes and evolutionary pressures.
• Population genetics: Detects targets of selective sweeps from population variation data using population genetics signals.
• Studies in model and non-model organisms: Applicable to both model and non-model systems where demographic, phenotypic, or functional background information is lacking.

Methodology:

Derives and computes a statistic from population genetics signals to identify the favored mutation within a selective sweep.