BEERS2

BEERS2 simulates realistic RNA-Seq reads through high-fidelity in silico modeling of the complete library preparation and sequencing pipeline to enable assessment, comparison, benchmarking, and development of bioinformatics tools.

Key Features:

• Flexible and Configurable Design: BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline.
• Transcript Input Options: BEERS2 takes input transcripts, typically full-length messenger RNA transcripts with polyA tails, from either customizable input or from CAMPAREE simulated RNA samples.
• Multiple Output Formats: BEERS2 produces realistic reads as FASTQ, SAM, or BAM formats, with SAM or BAM formats containing the true alignment to the reference genome, and also produces true transcript-level quantification values.
• Library Preparation Modeling: BEERS2 models polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in polymerase chain reaction (PCR) amplification, barcode read errors, and errors during PCR amplification.

Scientific Applications:

• Bioinformatics Tool Assessment: BEERS2 facilitates the assessment and benchmarking of bioinformatics tools through generation of realistic RNA-Seq reads with known ground truth.
• Algorithm Development: BEERS2 supports the development of new bioinformatics tools by providing realistic simulated data for testing and validation.
• Algorithm Comparison: BEERS2 enables direct comparison of bioinformatics tools under controlled, reproducible conditions with known transcript-level quantification values.
• Parameter Sensitivity Analysis: BEERS2 can measure the effect of simulation settings on specific algorithms, as demonstrated by analyzing the effect of several settings on the Salmon pseudoalignment algorithm.

Methodology:

BEERS2 takes input transcripts and produces realistic reads through detailed simulation of the library preparation and sequencing pipeline, including polyA selection or RiboZero ribosomal depletion, hexamer priming, PCR amplification with GC-content biases and PCR errors, and barcode read errors.