4.7 Article

A genomic random interval model for statistical analysis of genomic lesion data

Journal

BIOINFORMATICS
Volume 29, Issue 17, Pages 2088-2095

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt372

Keywords

-

Funding

  1. NCI
  2. NIGMS
  3. NHLBI of the National Institutes of Health [CA21765, U01GM 92666, U19HL065962]
  4. American Lebanese Syrian Associated Charities (ALSAC)
  5. NATIONAL CANCER INSTITUTE [P30CA021765] Funding Source: NIH RePORTER
  6. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [U19HL065962] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [U01GM092666] Funding Source: NIH RePORTER

Ask authors/readers for more resources

Motivation: Tumors exhibit numerous genomic lesions such as copy number variations, structural variations and sequence variations. It is difficult to determine whether a specific constellation of lesions observed across a cohort of multiple tumors provides statistically significant evidence that the lesions target a set of genes that may be located across different chromosomes but yet are all involved in a single specific biological process or function. Results: We introduce the genomic random interval (GRIN) statistical model and analysis method that evaluates the statistical significance of the abundance of genomic lesions that overlap a specific locus or a pre-defined set of biologically related loci. The GRIN model retains certain biologically important properties of genomic lesions that are ignored by other methods. In a simulation study and two example analyses of leukemia genomic lesion data, GRIN more effectively identified important loci as significant than did three methods based on a permutation-of-markers model. GRIN also identified biologically relevant pathways with a significant abundance of lesions in both examples.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available