Anise and BASIL

Methods for the detection and assembly of novel sequence in high-throughput sequencing data

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Large insertions of novel sequence are an important type of structural variants. Previous studies used traditional de novo assemblers for assembling non-mapping high-throughput sequencing (HTS) or capillary reads and then tried to anchor them in the reference using paired read information.


We present approaches for detecting insertion breakpoints and targeted assembly of large insertions from HTS paired data: BASIL and ANISE. On near identity repeats that are hard for assemblers, ANISE employs a repeat resolution step. This results in far better reconstructions than obtained by ABYSS. On simulated data, we found our insert assembler to be competitive with the de novo assembler ABYSS while yielding already anchored inserted sequence as opposed to unanchored contigs as from ABYSS. On real-world data, we detected novel sequence in a human individual and thoroughly validated the assembled sequence.