MeFiT

MeFiT merges and filters paired-end Illumina MiSeq 16S rRNA amplicon reads to produce high-quality sequences for microbial community analyses.

Key Features:

• Integrated merging and filtering pipeline: Performs overlapping paired-end read merging and quality-based filtering within a single computational workflow.
• Context-aware read merging (CASPER): Uses CASPER (context-aware scheme for paired-end reads) to merge paired-end reads by leveraging contextual information to improve merged-sequence accuracy.
• Quality filtering options: Implements filtering by traditional average Q-score and by maximum expected error cut-off threshold.
• Target data: Processes 16S rRNA amplicon sequences generated from Illumina MiSeq paired-end sequencing.
• Implementation: Implemented in Python.

Scientific Applications:

• Microbial ecology: Enables preprocessing of 16S rRNA amplicon data to support characterization of microbial communities.
• Diversity assessment: Provides high-quality input reads for alpha and beta diversity analyses.
• Taxonomic profiling: Produces merged, quality-filtered sequences suitable for taxonomic assignment workflows.
• Functional annotation studies: Supplies curated sequence data for downstream functional inference from amplicon-derived datasets.
• General paired-end read preprocessing: Applies to any analyses requiring precise processing of Illumina paired-end reads.

Methodology:

Uses CASPER for context-aware merging of overlapping paired-end reads and applies quality filtering based on average Q-scores or maximum expected error thresholds.