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Millions of DNA sequences (reads) are generated by Next Generation Sequencing machines every day. There is a need for high performance algorithms to map these sequences to the reference genome to identify single nucleotide polymorphisms or rare transcripts to fulfill the dream of personalized medicine. In this paper, the authors present a high-throughput parallel sequence mapping program pFANGS. pFANGS is designed to find all the matches of a query sequence in the reference genome tolerating a large number of mismatches or insertions/deletions. pFANGS partitions the computational workload and data among all the processes and employs load-balancing mechanisms to ensure better process efficiency.
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