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Background: Identifying all possible mapping locations of next-generationsequencing (NGS) reads is highly essential in several applications such asprediction of genomic variants or protein binding motifs located in repeatregions, isoform expression quantification, metagenomics analysis, etc.However, this task is very time-consuming and majority of mapping tools onlyfocus on one or a few best mapping locations. Results: We propose AMAS, analignment tool specialized in identifying all possible mapping locations of NGSreads in a reference sequence. AMAS features an effective use of adaptive seedsto speed up read mapping while preserving sensitivity. Specifically, an indexis designed to pre-store the locations of adaptive seeds in the referencesequence, efficiently reducing the time for seed matching and partitioning. Anaccurate filtration of adaptive seeds is further applied to substantiallytighten the candidate alignment space. As a result, AMAS runs several timesfaster than other state-of-the-art read mappers while achieving similaraccuracy. Conclusions: AMAS provides a valuable resource to speed up theimportant yet time-consuming task of identifying all mapping locations of NGSreads. AMAS is implemented in C++ based on the SeqAn library and is freelyavailable at https://sourceforge.net/projects/ngsamas/. Keywords:next-generation sequencing, read mapping, sequence alignment, adaptive seeds,seed partition, filtration

AMAS: Optimizing the Partition and Filtration of Adaptive Seeds to Speed up Read Mapping