Computer Science and Engineering
 Gothenburg University | Chalmers

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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.

Publications

Roy, Rajat S. and Bhattacharya, Debashish and Schliep , Alexander. Turtle: Identifying frequent k-mers with cache-efficient algorithms (2014) [details]

Mahmud, Md and Schliep, Alexander. TreQ-CG: Clustering Accelerates High-Throughput Sequencing Read Mapping (2014) [details]

Marshall, Tobias and Costa, Ivan and Canzar, Stefan and Bauer, Markus and Klau, Gunnar and Schliep, Alexander and Schönhuth, Alexander. CLEVER: Clique-Enumerating Variant Finder (2012) [details]

Roy, Rajat Shuvro and Chen, Kevin and Sengupta, Anirvan and Schliep, Alexander. SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding (2012) [details]

Mahmud, Md and Wiedenhoeft, John and Schliep, Alexander . Indel-tolerant Read Mapping with Trinucleotide Frequencies using Cache-Oblivious kd-Trees (2012) [details]

Marshall, Tobias and Costa, Ivan and Canzar, Stefan and Bauer, Markus and Klau, Gunnar and Schliep, Alexander and Schönhuth, Alexander. CLEVER: Clique-Enumerating Variant Finder (2012) [details]

Contact: Md P. Mahmud (pavelm@cs.rutgers.edu).