Genomics Inform.  2013 Mar;11(1):24-33. 10.5808/GI.2013.11.1.24.

Bioinformatics Interpretation of Exome Sequencing: Blood Cancer

Affiliations
  • 1Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 305-806, Korea. deepreds@kribb.re.kr
  • 2Department of Bioinformatics, University of Science and Technology, Daejeon 305-806, Korea.

Abstract

We had analyzed 10 exome sequencing data and single nucleotide polymorphism chips for blood cancer provided by the PGM21 (The National Project for Personalized Genomic Medicine) Award program. We had removed sample G06 because the pair is not correct and G10 because of possible contamination. In-house software somatic copy-number and heterozygosity alteration estimation (SCHALE) was used to detect one loss of heterozygosity region in G05. We had discovered 27 functionally important mutations. Network and pathway analyses gave us clues that NPM1, GATA2, and CEBPA were major driver genes. By comparing with previous somatic mutation profiles, we had concluded that the provided data originated from acute myeloid leukemia. Protein structure modeling showed that somatic mutations in IDH2, RASGEF1B, and MSH4 can affect protein structures.

Keyword

acute myeloid leukemia; computational biology; exome; mutation

MeSH Terms

Awards and Prizes
Computational Biology
Exome
Humans
Leukemia, Myeloid, Acute
Loss of Heterozygosity
Polymorphism, Single Nucleotide
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