An integrative approach to predicting the functional effects of non-coding and coding sequence variation

Abstract Motivation: Technological advances have enabled the identification of an increasingly large spectrum of single nucleotide variants within the human genome, many of which may be associated with monogenic disease or complex traits. Here, we propose an integrative approach, named FATHMM-MKL, to predict the functional consequences of both coding and non-coding sequence variants. Our method utilizes various genomic annotations, which have recently become available, and learns to weight the significance of each component annotation source. Results: We show that our method outperforms current state-of-the-art algorithms, CADD and GWAVA, when predicting the functional consequences of non-coding variants. In…

• DF
  Directorate for Biological Sciences
• MR
  Medical Research Council

  Awards: G1000427/1, MC_UU_12013, G1000427
• EA
  Engineering and Physical Sciences Research Council

  Awards: EP/K008250/1, EP/K008250/1, EP/M01715X/1
• BA
  Biotechnology and Biological Sciences Research Council

  Awards: BB/G022771/1, BB/L018543/1