CAFU is a Galaxy-based bioinformatics framework for comprehensive assembly and functional annotation of unmapped RNA-seq data from single- and mixed-species samples which integrates plenty of existing next-generation sequencing (NGS) analytical tools and our developed programs, and features an easy-to-use interface to manage, manipulate and most importantly, explore large-scale unmapped reads. Besides the common process of reads cleansing and mapping, unmapped reads extraction and de novo transcription assembly, CAFU optionally offers multiple-level evidence evaluation, sequence and expression characterization, and transcript function annotation. Taking advantages of machine learning (ML) technologies, CAFU also effectively addresses the challenge of classifying species-specific transcripts assembled using unmapped reads from mixed-species samples.

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