EXFI

EXFI predicts exon sequences and constructs splice graphs from assembled transcriptomes and raw whole-genome sequencing reads to characterize intron–exon boundaries and transcript structure in nonmodel organisms lacking a reference genome.

Key Features:

• Implementation: Implemented as a Python-based computational pipeline.
• Input data: Operates on assembled transcriptomes and raw whole-genome sequencing (WGS) reads.
• Bloom filter read filtering: Uses Bloom filters to filter sequencing reads not associated with the transcriptome.
• Intron–exon junction prediction: Predicts intron–exon junctions from filtered reads and assemblies.
• Exon identification: Identifies exon sequences from assembled transcriptome data.
• Splice graph construction: Constructs splice graphs that represent exon connectivity and transcript paths.
• Output format: Writes predicted exon sequences and their connectivity in GFA1 (Graphical Fragment Assembly v1) format.

Scientific Applications:

• Population genetics: Enables population genetic studies by maximizing the use of genomic information in nonmodel organisms without reference genomes.
• Transcript assembly analysis: Facilitates analysis of transcript assembly and alternative splicing via splice graphs.
• Genomic architecture characterization: Supports characterization of intron–exon boundaries and overall genomic structure in nonmodel species.

Methodology:

Filters raw WGS reads against assembled transcriptomes using Bloom filters, predicts intron–exon junctions and exon sequences from assemblies, constructs splice graphs, and outputs results in GFA1 format.