Jianqiao Hu a second-year doctoral candidate in the Graduate Program in Neuroscience at the University of Washington, co-advised by Dr. Bing Brunton and Dr. Edgar Walker. His research focus revolves around unraveling the intricate processes through which sensory information is represented in the brain, utilizing machine learning techniques. Before relocating to Seattle, Lawrence dedicated his efforts to improving the scalability of high-throughput sequencing data preprocessing, aiming to deepen our understanding of somatic recombination mechanisms.
We proposed and implemented TrieDedup to efficiently and accurately deduplicate high-throughput sequencing experiments while accounting for sequencing artifacts. TrieDedup uses trie (prefix tree) structure to compare and store sequences. Our benchmark experiments show TrieDedup can deduplicate reads up to 160-fold faster than pairwise comparison at a cost of 36-fold higher memory usage.
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