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Abstract

Next generation sequencing technologies produce massive amounts of sequence reads that are short and error prone. We have developed a machine learning based method, called QPALMA, which learns how to combine alignment information with quality scores, splice site predictions and intron length information. We show that the optimal combination leads to considerable improvements in alignment accuracy.