RNF

RNF standardizes the encoding of simulated read origins to enable consistent evaluation of Next-Generation Sequencing (NGS) mappers.

Key Features:

• Standardized Read Naming: Encodes positional metadata, including the original positions of reads within source genomes, using the Read Naming Format (RNF).
• Integration with Simulation Tools: MIShmash (part of RnfTools) converts outputs from DwgSim, Art, Mason, and CuReSim into RNF to ensure consistent metadata across simulators.
• Evaluation of Mappers: LAVEnder evaluates mappers using RNF-formatted reads with a focus on mapping qualities for parameterizing ROC curves and assessing the impact of sample contamination.

Scientific Applications:

• Mapper Evaluation: Enables direct, standardized comparison of alignment tools (NGS mappers) using simulated reads with known origins.
• Quality Assessment: Supports analysis of mapping qualities to tune mapper parameters and quantify alignment confidence.
• Contamination Analysis: Facilitates assessment of how sample contamination affects mapping quality and mapper performance.

Methodology:

Reads are simulated with DwgSim, Art, Mason, or CuReSim, converted into the RNF by MIShmash (RnfTools), and evaluated by LAVEnder which compares mapper outputs to RNF-encoded positional metadata focusing on mapping quality and contamination effects.