Detecting positive selection from genome scans of linkage disequilibrium

Journal ArticleThough a variety of linkage disequilibrium tests have recently been introduced to measure the signal of recent positive selection, the statistical properties of the various methods have not been directly compared. While most applications of these tests have suggested that positive selection has played an important role in recent human history, the results of these tests have varied dramatically

Detecting positive selection from genome scans of linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Though a variety of linkage disequilibrium tests have recently been introduced to measure the signal of recent positive selection, the statistical properties of the various methods have not been directly compared. While most applications of these tests have suggested that positive selection has played an important role in recent human history, the results of these tests have varied dramatically.</p> <p>Results</p> <p>Here, we evaluate the performance of three statistics designed to detect incomplete selective sweeps, LRH and iHS, and ALnLH. To analyze the properties of these tests, we introduce a new computational method that can model complex population histories with migration and changing population sizes to simulate gene trees influenced by recent positive selection. We demonstrate that iHS performs substantially better than the other two statistics, with power of up to 0.74 at the 0.01 level for the variation best suited for full genome scans and a power of over 0.8 at the 0.01 level for the variation best suited for candidate gene tests. The performance of the iHS statistic was robust to complex demographic histories and variable recombination rates. Genome scans involving the other two statistics suffer from low power and high false positive rates, with false discovery rates of up to 0.96 for ALnLH. The difference in performance between iHS and ALnLH, did not result from the properties of the statistics, but instead from the different methods for mitigating the multiple comparison problem inherent in full genome scans.</p> <p>Conclusions</p> <p>We introduce a new method for simulating genealogies influenced by positive selection with complex demographic scenarios. In a power analysis based on this method, iHS outperformed LRH and ALnLH in detecting incomplete selective sweeps. We also show that the single-site iHS statistic is more powerful in a candidate gene test than the multi-site statistic, but that the multi-site statistic maintains a low false discovery rate with only a minor loss of power when applied to a scan of the entire genome. Our results highlight the need for careful consideration of multiple comparison problems when evaluating and interpreting the results of full genome scans for positive selection.</p

Identifying and Characterizing Genetic Variants Associated with Colorectal Cancer

https://openworks.mdanderson.org/sumexp23/1113/thumbnail.jp

Association Between Rare TP53 variants and Cancer Predisposition in Colorecta, Melanoma, Ovarian, Pancreatic, and Prostate Cancer

https://openworks.mdanderson.org/sumexp22/1060/thumbnail.jp

Ancestral alleles and population origins: Inferences depend on mutation rate

Previous studies have found that at most human loci, ancestral alleles are African, in the sense that they reach their highest frequency there. Conventional wisdom holds that this reflects a recent African origin of modern humans. This paper challenges that view by showing that the empirical pattern (of elevated allele frequencies within Africa) is not as pervasive as has been thought. We confirm this African bias in a set of mainly protein-coding loci, but find a smaller bias in Alu insertion polymorphisms, and an even smaller bias in noncoding loci. Thus, the strong bias that was originally observed must reflect some factor that varies among data sets - something other than population history. This factor may be the per-locus mutation rate: the African bias is most pronounced in loci where this rate is high. The distribution of ancestral alleles among populations has been studied using 2 methods. One of these involves comparing the fractions of loci that reach maximal frequency in each population. The other compares the average frequencies of ancestral alleles. The first of these methods reflects history in a manner that depends on the mutation rate. When that rate is high, ancestral alleles at most loci reach their highest frequency in the ancestral population. When that rate is low, the reverse is true. The other method - comparing averages - is unresponsive. Average ancestral allele frequencies are affected neither by mutation rate nor by the history of population size and migration. In the absence of selection and ascertainment bias, they should be the same everywhere. This is true of one data set, but not of 2 others. This also suggests the action of some factor, such as selection or ascertainment bias, that varies among data sets. © The Author 2007. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved

Inferring Population Continuity Versus Replacement with aDNA: A Cautionary Tale from the Aleutian Islands

In The Aleutian and Commander Islands and Their Inhabitants (Philadelphia: Wistar Institute of Anatomy and Biology, 1945), Hrdlička proposed a population replacement event in the Aleutian Islands approximately 1,000 years ago based on a perceived temporal shift in cranial morphology. However, the archaeological record indicates cultural, and presumed population, continuity for more than 4,000 years. We use mtDNA haplogroup data in the series of prehistoric eastern Aleutian samples (n = 86) studied craniometrically by Hrdlička to test alternative hypotheses regarding population continuity or replacement in the region. This molecular characterization, in conjunction with direct dating of individual specimens, provided increased resolution for hypothesis testing. Results indicate an apparent shift in mtDNA haplogroup frequencies in the eastern Aleutians approximately 1,000 years ago, in concert with changes in mortuary practices and isotopic signatures reflecting resource acquisition strategies. The earliest Aleut populations were characterized by a high frequency of haplogroup A, as are most modern populations of the North American arctic. Later prehistoric peoples in the Aleutians were characterized by a high frequency of haplogroup D and a correspondingly lower frequency of haplogroup A, a pattern typified by modern Aleut populations

Personalized Risk Assessment in Never, Light, and Heavy Smokers in a prospective cohort in Taiwan.

The objective of this study was to develop markedly improved risk prediction models for lung cancer using a prospective cohort of 395,875 participants in Taiwan. Discriminatory accuracy was measured by generation of receiver operator curves and estimation of area under the curve (AUC). In multivariate Cox regression analysis, age, gender, smoking pack-years, family history of lung cancer, personal cancer history, BMI, lung function test, and serum biomarkers such as carcinoembryonic antigen (CEA), bilirubin, alpha fetoprotein (AFP), and c-reactive protein (CRP) were identified and included in an integrative risk prediction model. The AUC in overall population was 0.851 (95% CI = 0.840-0.862), with never smokers 0.806 (95% CI = 0.790-0.819), light smokers 0.847 (95% CI = 0.824-0.871), and heavy smokers 0.732 (95% CI = 0.708-0.752). By integrating risk factors such as family history of lung cancer, CEA and AFP for light smokers, and lung function test (Maximum Mid-Expiratory Flow, MMEF25-75%), AFP and CEA for never smokers, light and never smokers with cancer risks as high as those within heavy smokers could be identified. The risk model for heavy smokers can allow us to stratify heavy smokers into subgroups with distinct risks, which, if applied to low-dose computed tomography (LDCT) screening, may greatly reduce false positives

Banner News

https://openspace.dmacc.edu/banner_news/1275/thumbnail.jp

Truncating the Y-Axis: Threat or Menace?

Bar charts with y-axes that don't begin at zero can visually exaggerate effect sizes. However, advice for whether or not to truncate the y-axis can be equivocal for other visualization types. In this paper we present examples of visualizations where this y-axis truncation can be beneficial as well as harmful, depending on the communicative and analytic intent. We also present the results of a series of crowd-sourced experiments in which we examine how y-axis truncation impacts subjective effect size across visualization types, and we explore alternative designs that more directly alert viewers to this truncation. We find that the subjective impact of axis truncation is persistent across visualizations designs, even for designs with explicit visual cues that indicate truncation has taken place. We suggest that designers consider the scale of the meaningful effect sizes and variation they intend to communicate, regardless of the visual encoding