EARRINGS

EARRINGS performs de novo adapter detection and trimming of next-generation sequencing (NGS) reads to enable consistent preprocessing for cross-sample comparisons and large-scale meta-analyses.

Key Features:

• No A Priori Adapter Sequences Required: EARRINGS detects and trims adapter sequences without requiring candidate adapter inputs, enabling processing of datasets where adapters are undocumented in GEO or SRA.
• High Accuracy and Throughput: Benchmarks against existing adapter trimmers show comparable trimming accuracy while achieving higher throughput.
• Implementation: Implemented in modern C++ and optimized with SIMD and multithreading for high-performance processing of large NGS batches.

Scientific Applications:

• Large-scale meta-analyses: Provides consistent adapter trimming across datasets to support comparative analyses spanning multiple studies.
• Cross-sample comparisons: Removes reliance on predefined adapter sequences to reduce preprocessing variability in cross-sample and cross-study comparisons.
• Repository data preprocessing: Enables trimming of NGS data from repositories such as GEO and SRA where adapter documentation is often missing or inaccurate.

Methodology:

De novo adapter detection and trimming algorithms that operate without candidate adapter inputs, implemented in modern C++ with SIMD and multithreading and benchmarked against existing adapter trimmers.