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A Bayesian statistical method was developed to assess the noteworthiness of a single nucleotide polymorphism (SNP)-phenotype association that shows statistical significance in various observational studies, but it has seldom been ...
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A Bayesian statistical method was developed to assess the noteworthiness of a single nucleotide polymorphism (SNP)-phenotype association that shows statistical significance in various observational studies, but it has seldom been applied to GWAS meta-analyses in cancers. Data (i.e. allelic frequency, odds ratio, 95% confidence interval, etc.) on various SNP-cancer associations were extracted from meta-analysis of GWAS and the National Human Genome Research Institute (NHGRI) Catalog of Published GWAS and were used to compute the false positive report probability (FPRP) and Bayesian false discovery probability (BFDP) to evaluate the noteworthiness of SNP-cancer associations. Independent paired t-tests showed a direct relationship between SNP cancer P-values and both FPRP and BFDP estimates. However, a discrepancy in the number of noteworthy associations between P-value comparison and either FPRP or BFDP was found using data extracted from meta analyses of GWAS and the GWAS Catalog. Most P-values of associations with nonsignificant P-values but with noteworthy FPRP and BFDP estimates were within the range of 10(-6) to 5 x 10(-8). A poorly selected genome-wide significance threshold and inclusion of a nonsignificant SNP-phenotype association into the noteworthy test can, with either noteworthy FPRP or BFDP computation, give a false impression of noteworthiness for a nonsignificant association.
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To provide an up-to-date summary of multiple sclerosis-susceptible gene variants and assess the noteworthiness in hopes of finding true associations, we investigated the results of 44 meta-analyses on gene variants and multiple sc...
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To provide an up-to-date summary of multiple sclerosis-susceptible gene variants and assess the noteworthiness in hopes of finding true associations, we investigated the results of 44 meta-analyses on gene variants and multiple sclerosis published through December 2016. Out of 70 statistically significant genotype associations, roughly a fifth (21%) of the comparisons showed noteworthy false-positive rate probability (FPRP) at a statistical power to detect an OR of 1.5 and at a prior probability of 10(-6) assumed for a random single nucleotide polymorphism. These associations (IRF8/rs17445836, STAT3/rs744166, HLA/rs4959093, HLA/rs2647046, HLA/rs7382297, HLA/rs17421624, HLA/rs2517646, HLA/rs9261491, HLA/rs2857439, HLA/rs16896944, HLA/rs3132671, HLA/rs2857435, HLA/rs9261471, HLA/rs2523393, HLA-DRB1/rs3135388, RGS1/rs2760524, PTGER4/rs9292777) also showed a noteworthy Bayesian false discovery probability (BFDP) and one additional association (CD24 rs8734/rs52812045) was also noteworthy via BFDP computation. Herein, we have identified several noteworthy biomarkers of multiple sclerosis susceptibility. We hope these data are used to study multiple sclerosis genetics and inform future screening programs.
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Systemic lupus erythematosus (SLE) is a multi-systemic severe autoimmune disease which results from the irreversible loss of self-tolerance and impaired molecular responses, especially an altered interferon signature. We synthesiz...
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Systemic lupus erythematosus (SLE) is a multi-systemic severe autoimmune disease which results from the irreversible loss of self-tolerance and impaired molecular responses, especially an altered interferon signature. We synthesized all meta-analyses reporting a genetic association of SLE, and further investigated their validity to discover false positive results under Bayesian methods. We executed a PubMed search to extract the respective results regarding gene polymorphisms of SLE, published until June 30th 2017 and selected a single result per genetic variant among duplicates. Among 133 significant genotype comparisons, 45 (34%) were found noteworthy under both false positive report probability (FPRP) and Bayesian false discovery probability (BFDP). From the meta-analysis of genome-wide association studies (GWAS), we could confirm that all significant comparisons were noteworthy under both Bayesian approaches. Both approaches may be advantageous for determining whether the reported associations are genuine, especially for interpreting results from observational studies instead of GWAS whose significance was determined in a more strict manner. When determining results from GWAS with a p-value ranging between 0.05 and 5 x 10(-8), other statistical approaches, rather than single standard significance may be beneficial. Taking into account these considerations, a proportion of meta-analyses claimed statistical significance, but these results need to be interpreted with caution. (C) 2018 Published by Elsevier B.V.
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This paper presents a new dynamic phasor (DP) model of a modular multilevel converter (MMC) with extended frequency range for direct interfacing to an electromagnetic transient (EMT) simulator. The internal dynamics of the MMC are...
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This paper presents a new dynamic phasor (DP) model of a modular multilevel converter (MMC) with extended frequency range for direct interfacing to an electromagnetic transient (EMT) simulator. The internal dynamics of the MMC are modeled considering dominant harmonic components of each variable. To model the external dynamics of the converter, a novel construct referred to as a base-frequency DP is employed, which allows to capture and model any number of frequency components of external variables without a significant increase in computational burden. The proposed model is validated against detailed EMT models by comparing its results for an inverter system, a back-to-back high-voltage direct current system, and a 12-bus power system built in PSCAD/EMTDC simulator. Simulation results prove that the new model is significantly more computationally efficient than existing models and is capable of maintaining a high level of accuracy. Experimental verification on a scaled-down laboratory setup is also included.
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