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

Genome biology | Feb 17, 2010

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 RIS Download

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

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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

Mouse Genome Informatics (Data, Gene Annotation)

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