Blue

Blue performs error correction of short-read sequencing data using k-mer consensus and context analysis to improve data quality for genome assembly and alignment.

Key Features:

• Error Correction Capabilities: Detects and corrects substitutions, insertions, deletions, and uncalled bases in short reads.
• Format Compatibility: Supports FASTQ and FASTA inputs and updates base quality scores for bases it modifies.
• Read Pairing Maintenance: Maintains read pairing within files and between paired files to preserve paired-end relationships.
• Performance and Scalability: Implements memory-efficient, fast algorithms suitable for large sequencing datasets and is reported to outperform other published error-correction algorithms in speed and accuracy.
• Cross-Correction Capability: Uses a k-mer consensus table derived from one dataset to correct another dataset, enabling correction of small long-read sets such as 454 mate-pair reads with larger Illumina datasets.
• Platform Compatibility: Implemented in C# and runs natively on Windows or under Mono on Linux.

Scientific Applications:

• Genome assembly: Reduces sequencing errors to improve contig length and overall assembly accuracy.
• Sequence alignment: Improves read quality to enable more accurate alignments.
• Long-read enhancement and finishing: Enhances small sets of long reads (e.g., 454 mate-pair reads) via cross-correction with Illumina reads to improve assemblies and finished-genome quality.

Methodology:

Employs k-mer consensus and context analysis and supports a decoupled approach where the k-mer consensus table can be derived from an external dataset for cross-correction.