Signal localization: a new approach in signal discovery

Abstract

A new approach for statistical association signal identification is developed in this paper. We consider a strategy for nonprecise signal identification by extending the well-known signal detection and signal identification methods applicable to the multiple testing problem. Collection of statistical instruments under the presented approach is much broader than under the traditional signal identification methods, allowing more efficient signal discovery. Further assessments of maximal value and average statistics in signal discovery are improved. While our method does not attempt to detect individual predictors, it instead detects sets of predictors that are jointly associated with the outcome. Therefore, an important application would be in genome wide association study (GWAS), where it can be used to detect genes which influence the phenotype but do not contain any individually significant single nucleotide polymorphism (SNP). We compare power of the signal identification method based on extremes of single p-values with the signal localization method based on average statistics for logarithms of p-values. A simulation analysis informs the application of signal localization using the average statistics for wide signals discovery in Gaussian white noise process. We apply average statistics and the localization method to GWAS to discover better gene influences of regulating loci in a Chinese cohort developed for risk of nasopharyngeal carcinoma (NPC).

A Genome-Wide Association Study Reveals a BDNF-Centered Molecular Network Associated with Alcohol Dependence and Related Clinical Measures

“…In the next step, we performed a genome-wide screening for associations of the AD phenotype and regions in the genome by using Fisher’s combined test statistics integrated within the signal localization approach [ 37 ]. We used sliding localization windows of sizes 21 (radius = 10), 41 (radius = 20), 71 (radius = 35), 101 (radius = 50), and 201 (radius = 50) SNPs, as well as 100 thousand (K) (radius = 50K) and 200K (radius = 100 K) base pairs centered at all loci of genetic markers available.…”

A Genome-Wide Association Study Reveals New Genes in a Molecular Network Associated With Alcohol Dependence and Related Clinical Measures

“…In the next step, we performed a genome-wide screening for associations of the AD phenotype and regions in the genome by using Fisher's combined test statistics integrated within the signal localization approach [22]. We used sliding localization windows of sizes 21 (radius=10), 41 (radius =20), 71 (radius =35), 101 (radius =50), and 201 (radius =50) SNPs, as well as 100 thousand (K) (radius =50K) and 200K (radius =100K) base pairs centered at all loci of genetic markers available.…”