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Improved variant discovery through local re-alignment of short-read next-generation sequencing data using SRMA.

A primary component of next-generation sequencing analysis is to align short reads to a reference genome, with each read aligned independently. However, reads that observe the same non-reference DNA sequence are highly correlated and can be used to better model the true variation in the target genome. A novel short-read micro realigner, SRMA, that leverages this correlation to better resolve a consensus of the underlying DNA sequence of the targeted genome is described here.

Pubmed ID: 20932289

Authors

  • Homer N
  • Nelson SF

Journal

Genome biology

Publication Data

February 17, 2010

Associated Grants

  • Agency: NIMH NIH HHS, Id: R01 MH071852
  • Agency: NIMH NIH HHS, Id: R01 MH071852
  • Agency: NHGRI NIH HHS, Id: U01HG005210
  • Agency: NINDS NIH HHS, Id: U24 NS052108
  • Agency: NINDS NIH HHS, Id: U24NS052108

Mesh Terms

  • Algorithms
  • Base Sequence
  • Cell Line, Tumor
  • Computational Biology
  • Gene Frequency
  • Genome, Human
  • Humans
  • Oligonucleotide Array Sequence Analysis
  • Polymorphism, Single Nucleotide
  • Sequence Alignment
  • Sequence Analysis, DNA