HTSMethods: Analysis of high-throughput sequencing data
Next generation sequencing experiments produce millions of short reads from target genomes in a cost-efficient manner. Higher throughput brings new challenges such as how to map these short reads efficiently and how to deal with errors introduced by sequencing machines. Currently, we are investigating the problem of read-mapping in an indel-tolerant manner. We are also looking for techniques which will efficiently map reads back to reference genome.
For further information contact Md P. Mahmud (email@example.com). This project is connected to the following projects: TreQ, SLiQ, Turtle, TreqCG, AlgoEngineering.
Members: Md P. Mahmud, John Wiedenhoeft. Collaborators: Alexander Schönhuth (Centrum Wiskunde & Informatica), Gunnar Klau (Centrum Wiskunde & Informatica), Debashish Bhattacharya (Department of Ecology, Evolution, and Natural Resources, Rutgers), Shridar Ganesan (The Cancer Institute of New Jersey), Kevin Chen (Department of Genetics, Rutgers).
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