Bioinformatics Interpretation of Exome Sequencing: Blood Cancer

  • Kim J
  • Lee Y
  • Kim N
N/ACitations
Citations of this article
26Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Kim, J., Lee, Y.-G., & Kim, N. (2013). Bioinformatics Interpretation of Exome Sequencing: Blood Cancer. Genomics & Informatics, 11(1), 24. https://doi.org/10.5808/gi.2013.11.1.24

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free