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  1. Method: A general framework for identifying oligogenic combinations of rare variants in complex disorders
    • Vijay Kumar Pounraja and
    • Santhosh Girirajan
    Genome Res. May 2022 32: 904-915; Published in Advance March 17, 2022, doi:10.1101/gr.276348.121
    ...or their aggregate burden in affected individuals compared to controls. However, these studies overlook the influence of combinations of rare variants that may not be deleterious on their own due to statistical challenges resulting from rarity and combinatorial explosion when enumerating variant combinations...
  2. Perspective: From human genome to cancer genome: The first decade
    • David A. Wheeler and
    • Linghua Wang
    Genome Res. July 2013 23: 1054-1062; doi:10.1101/gr.157602.113
    ...) Frequency classification of tumors. The pie charts divide the patients into three groups based on frequency of nonsilentmutation: 0 detectable somaticmutations, less than 30, and greater than or equal to 30 for selected representative tumor types (30 mutations represent a frequency of 1 per Mbp in A...
  3. Method: Prioritizing candidate disease genes by network-based boosting of genome-wide association data
    • Insuk Lee,
    • U. Martin Blom,
    • Peggy I. Wang,
    • Jung Eun Shim,
    • and Edward M. Marcotte
    Genome Res. July 2011 21: 1109-1121; Published in Advance May 2, 2011, doi:10.1101/gr.118992.110
    ...genes in a more efficient manner. A typical GWAS analysis involves comparing case and control individuals at selected single nucleotide polymorphisms (SNPs) or, more recently, copy number variants (CNVs). SNPs representing common haplotype blocks are measured wide (at approximately 500...
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