75 research outputs found
Transferable tax credits in Missouri: an analytical review
No full textIn 2005, Missouri had 53 legally authorized tax credit programs. In this paper, the authors assemble basic information on all of these programs and further analyze the six largest (by tax credits issued) that include freely transferable credits. Their analysis focuses on the institutional features of these programs, the kinds of market failures or disparities they may address, and whether the design of each program is consistent with its economic rationale. The authors also consider whether the evaluation of each program by the state is consistent with its economic rationale. They conclude with a brief discussion of the transactions prices for the credits on which they have data and whether making the tax credits refundable as well as transferable could reduce the transactions costs associated with these programs.Tax credits ; Economic development ; Missouri
Catherine N. Wineinger: Gendering the GOP: Intraparty Politics and Republican Women’s Representation in Congress
No full textBook reviewed: Catherine N. Wineinger 2022. Gendering the GOP: Intraparty Politics and Republican Women’s Representation in Congress. Oxford University Press. 27.95 paper. 220 pages.This article is published as Kedrowski, K.M., Wineinger, Catherine N. Gendering the GOP: Intraparty Politics and Republican Women’s Representation in Congress. In The Forum: A Journal of Applied Research in Contemporary Politics. February 2023, 21(1). https://doi.org/10.1515/for-2023-2007.© 2023 the author(s)This work is licensed under the Creative Commons Attribution 4.0 International License
Statistical methods in the analysis of copy number variation data
No full textCopy number variation is a significant form of genetic variation that has been shown to influence many traits. However, current methods used to estimate copy number variation are imprecise and prone to errors. This property is demonstrated in a study examining copy number variation in African Americans recruited into the Hypertensive Genetic Epidemiology Network study, and who were genotyped on the Affymetrix 6.0 array. The effect this has on downstream association analyses is explored, an alternative methods are proposed. Finally, a method is proposed that uses linkage disequilibrium between copy number variants and single nucleotide polymorphisms to improve the accuracy of copy number variation calling algorithms. The derivation of the linkage disequilibrium statistic is presented, and its properties are explored. The results of this dissertation will assist copy number variation researchers in future analyses
The impact of errors in copy number variation detection algorithms on association results.
No full textThe inaccuracy of copy number variation (CNV) detection on single nucleotide polymorphism (SNP) arrays has recently been brought to attention. Such high error rates will undoubtedly have ramifications on downstream association testing. We examined this effect for a wide range of scenarios and found a noticeable decrease in power for error rates typical of CNV calling algorithms. We compared power using CNV calls to the log relative ratio and found the latter to be superior when error rates are moderate to large or when the CNV size is small. It is our recommendation that CNV researchers use intensity measurements as an alternative to CNV calls in these scenarios
A method to assess linkage disequilibrium between CNVs and SNPs inside copy number variable regions
No full textSince the discovery of the ubiquitous contribution of copy number variation to genetic variability, researchers have commonly used metrics such as r-squared to quantify linkage disequilibrium (LD) between copy number variants (CNVs) and single nucleotide polymorphisms (SNPs). However, these reports have been restricted to SNPs outside copy number variable regions (CNVR) as current methods have not been adapted to account for SNPs displaying variable copy number. We show that traditional LD metrics inappropriately quantify SNP/CNV covariance when SNPs lie within copy number variable regions (CNVR). We derive a new method for measuring LD that solves this issue, and defaults to traditional metrics otherwise. Finally, we present a procedure to estimate CNV-SNP allele frequencies from unphased CNV-SNP genotypes. Our method allows researchers to include all SNPs in SNP/CNV LD measurements, regardless of copy number
Recovery rate of deletions (red) and duplications (blue) from PennCNV using simulated intensity measurements as a function of CNV size.
No full text<p>Recovery rate of deletions (red) and duplications (blue) from PennCNV using simulated intensity measurements as a function of CNV size.</p
Simulated statistical power to detect an association with a putative CNV as a function of false negative rate (ν<sub>n</sub>).
No full text<p>The CNV explains 1% of the phenotypic variation when present in 20% of the population. The CNV has a frequency of 1% (red), 5% (orange), 10% (green), or 20% (blue). False positive rate (ν<sub>p</sub>) is zero.</p
Square root of the variance of Δ for the deletion and duplication CNV loci with and false negative (ν<sub>n</sub>) and false positive error rates (ν<sub>p</sub>).
No full text<p>Square root of the variance of Δ for the deletion and duplication CNV loci with and false negative (ν<sub>n</sub>) and false positive error rates (ν<sub>p</sub>).</p
Identification of allelic heterogeneity at type-2 diabetes loci and impact on prediction.
No full textAlthough over 60 single nucleotide polymorphisms (SNPs) have been identified by meta-analysis of genome-wide association studies for type-2 diabetes (T2D) among individuals of European descent, much of the genetic variation remains unexplained. There are likely many more SNPs that contribute to variation in T2D risk, some of which may lie in the regions surrounding established SNPs--a phenomenon often referred to as allelic heterogeneity. Here, we use the summary statistics from the DIAGRAM consortium meta-analysis of T2D genome-wide association studies along with linkage disequilibrium patterns inferred from a large reference sample to identify novel SNPs associated with T2D surrounding each of the previously established risk loci. We then examine the extent to which the use of these additional SNPs improves prediction of T2D risk in an independent validation dataset. Our results suggest that multiple SNPs at each of 3 loci contribute to T2D susceptibility (TCF7L2, CDKN2A/B, and KCNQ1; p<5×10(-8)). Using a less stringent threshold (p<5×10(-4)), we identify 34 additional loci with multiple associated SNPs. The addition of these SNPs slightly improves T2D prediction compared to the use of only the respective lead SNPs, when assessed using an independent validation cohort. Our findings suggest that some currently established T2D risk loci likely harbor multiple polymorphisms which contribute independently and collectively to T2D risk. This opens a promising avenue for improving prediction of T2D, and for a better understanding of the genetic architecture of T2D
A framework for smartphone-enabled, patient-generated health data analysis
No full textBackground: Digital medicine and smartphone-enabled health technologies provide a novel source of human health and human biology data. However, in part due to its intricacies, few methods have been established to analyze and interpret data in this domain. We previously conducted a six-month interventional trial examining the efficacy of a comprehensive smartphone-based health monitoring program for individuals with chronic disease. This included 38 individuals with hypertension who recorded 6,290 blood pressure readings over the trial. Methods: In the present study we provide a hypothesis testing framework for unstructured time series data, typical of patient-generated mobile device data. We used a mixed model approach for unequally spaced repeated measures using autoregressive and generalized autoregressive models, and applied this to the blood pressure data generated in this trial. Results: We were able to detect, roughly, a 2 mmHg decrease in both systolic and diastolic blood pressure over the course of the trial despite considerable intra- and inter-individual variation. Furthermore, by supplementing this finding by using a sequential analysis approach, we observed this result over three months prior to the official study end – highlighting the effectiveness of leveraging the digital nature of this data source to form timely conclusions. Conclusions: Health data generated through the use of smartphones and other mobile devices allow individuals the opportunity to make informed health decisions, and provide researchers the opportunity to address innovative health and biology questions. The hypothesis testing framework we present can be applied in future studies utilizing digital medicine technology or implemented in the technology itself to support the quantified self. The study was registered at clinicaltrials.gov (NCT01975428).</jats:p
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