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2016 ; 17 Suppl 2
(Suppl 2
): 5
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Pathway-based analyses
#MMPMID26867108
Kent JW Jr
BMC Genet
2016[Feb]; 17 Suppl 2
(Suppl 2
): 5
PMID26867108
show ga
BACKGROUND: New technologies for acquisition of genomic data, while offering
unprecedented opportunities for genetic discovery, also impose severe burdens of
interpretation and penalties for multiple testing. METHODS: The Pathway-based
Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of
multiple-testing burden through various approaches to aggregation of
highdimensional data in pathways informed by prior biological knowledge. RESULTS:
Experimental methods testedincluded the use of "synthetic pathways" (random sets
of genes) to estimate power and false-positive error rate of methods applied to
simulated data; data reduction via independent components analysis,
single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to
estimate genetic similarity; and general assessment of the efficacy of prior
biological knowledge to reduce the dimensionality of complex genomic data.
CONCLUSIONS: The work of this group explored several promising approaches to
managing high-dimensional data, with the caveat that these methods are
necessarily constrained by the quality of external bioinformatic annotation.
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