VaDiR: an integrated approach to Variant Detection in RNA | Zendy

Lisa Neums | Zendy; Seiji Suenaga | Zendy; Peter Beyerlein | Zendy; Sara Anders | Zendy; Devin C. Koestler | Zendy; Andrea Mariani | Zendy; Jeremy Chien | Zendy

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VaDiR: an integrated approach to Variant Detection in RNA

Author(s) -

Lisa Neums,

Seiji Suenaga,

Peter Beyerlein,

Sara Anders,

Devin C. Koestler,

Andrea Mariani,

Jeremy Chien

Publication year - 2017

Publication title -

gigascience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.947

H-Index - 54

ISSN - 2047-217X

DOI - 10.1093/gigascience/gix122

Subject(s) - dna sequencing , computational biology , exome , biology , genetics , exome sequencing , genome , rna , gene , mutation rate , mutation

Advances in next-generation DNA sequencing technologies are now enabling detailed characterization of sequence variations in cancer genomes. With whole-genome sequencing, variations in coding and non-coding sequences can be discovered. But the cost associated with it is currently limiting its general use in research. Whole-exome sequencing is used to characterize sequence variations in coding regions, but the cost associated with capture reagents and biases in capture rate limit its full use in research. Additional limitations include uncertainty in assigning the functional significance of the mutations when these mutations are observed in the non-coding region or in genes that are not expressed in cancer tissue.

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