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Department of Computer Science, Department of Statistics, Brigham Young University, Provo, UT 84602, USA. nathanlclement@gmail.com
The advent of next-generation sequencing technologies has increased the accuracy and quantity of sequence data, opening the door to greater opportunities in genomic research.
In this article, we present GNUMAP (Genomic Next-generation Universal MAPper), a program capable of overcoming two major obstacles in the mapping of reads from next-generation sequencing runs. First, we have created an algorithm that probabilistically maps reads to repeat regions in the genome on a quantitative basis. Second, we have developed a probabilistic Needleman-Wunsch algorithm which utilizes _prb.txt and _int.txt files produced in the Solexa/Illumina pipeline to improve the mapping accuracy for lower quality reads and increase the amount of usable data produced in a given experiment.
The source code for the software can be downloaded from http://dna.cs.byu.edu/gnumap.
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