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This content will become publicly available on April 17, 2015

Title: Defining window-boundaries for genomic analyses using smoothing spline techniques

High-density genomic data is often analyzed by combining information over windows of adjacent markers. Interpretation of data grouped in windows versus at individual locations may increase statistical power, simplify computation, reduce sampling noise, and reduce the total number of tests performed. However, use of adjacent marker information can result in over- or under-smoothing, undesirable window boundary specifications, or highly correlated test statistics. We introduce a method for defining windows based on statistically guided breakpoints in the data, as a foundation for the analysis of multiple adjacent data points. This method involves first fitting a cubic smoothing spline to the data and then identifying the inflection points of the fitted spline, which serve as the boundaries of adjacent windows. This technique does not require prior knowledge of linkage disequilibrium, and therefore can be applied to data collected from individual or pooled sequencing experiments. Moreover, in contrast to existing methods, an arbitrary choice of window size is not necessary, since these are determined empirically and allowed to vary along the genome.
 [1] ;  [2] ;  [3] ;  [4] ;  [3]
  1. Univ. of California, Davis, CA (United States). Dept. Plant Sciences.
  2. Univ. of Wisconsin, Madison, WI (United States). Dept. of Animal Sciences and Dept. of Biostatistics and Medical Information.
  3. Univ. of Wisconsin, Madison, WI (United States). Dept. of Agronomy and Dept. of Energy Great Lakes Bioenergy Research Center.
  4. Univ. of Wisconsin, Madison, WI (United States). Dept. of Animal Sciences, Dept. of Biostatistics and Medical Information and Dept. of Dairy Science.
Publication Date:
OSTI Identifier:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Genetics Selection Evolution (Online)
Additional Journal Information:
Journal Name: Genetics Selection Evolution (Online); Journal Volume: 47; Journal Issue: 1; Journal ID: ISSN 1297-9686
BioMed Central
Research Org:
Univ. of Wisconsin, Madison, WI (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States