scholarly journals Recessive deleterious variation has a limited impact on signals of adaptive introgression in human populations

2020 ◽  
Author(s):  
Xinjun Zhang ◽  
Bernard Kim ◽  
Kirk E. Lohmueller ◽  
Emilia Huerta-Sánchez
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Genomic Variation ◽  
Human Populations ◽  
Deleterious Mutations ◽  
Modern Humans ◽  
Recombination Rates ◽  
Limited Impact ◽  
Adaptive Mutations ◽  
Adaptive Introgression

AbstractAdmixture with archaic hominins has altered the landscape of genomic variation in modern human populations. Several gene regions have been previously identified as candidates of adaptive introgression (AI) that facilitated human adaptation to specific environments. However, simulation-based studies have suggested that population genetics processes other than adaptive mutations, such as heterosis from recessive deleterious variants private to populations before admixture, can also lead to patterns in genomic data that resemble adaptive introgression. The extent to which the presence of deleterious variants affect the false-positive rate and the power of current methods to detect AI has not been fully assessed. Here, we used extensive simulations to show that recessive deleterious mutations can increase the false positive rates of tests for AI compared to models without deleterious variants. We further examined candidates of AI in modern humans identified from previous studies and show that, although deleterious variants may hinder the performance of AI detection in modern humans, most signals remained robust when deleterious variants are included in the null model. While deleterious variants may have a limited impact on detecting signals of adaptive introgression in humans, we found that at least two AI candidate genes, HYAL2 and HLA, are particularly susceptible to high false positive rates due to the recessive deleterious mutations. By quantifying parameters that affect heterosis, we show that the high false positives are largely attributed to the high exon densities together with low recombination rates in the genomic regions, which can further be exaggerated by the population growth in recent human evolution. Although the combination of such parameters is rare in the human genome, caution is still warranted in other species with different genomic composition and demographic histories.

scholarly journals The Impact of Recessive Deleterious Variation on Signals of Adaptive Introgression in Human Populations

Genetics ◽  
2020 ◽  
Vol 215 (3) ◽  
pp. 799-812 ◽  
Author(s):  
Xinjun Zhang ◽  
Bernard Kim ◽  
Kirk E. Lohmueller ◽  
Emilia Huerta-Sánchez
Keyword(s):  
Human Genome ◽  
False Positive ◽  
False Positive Rate ◽  
Genomic Variation ◽  
Human Populations ◽  
Deleterious Mutations ◽  
Recombination Rates ◽  
Adaptive Mutations ◽  
Adaptive Introgression ◽  
The Impact

Admixture with archaic hominins has altered the landscape of genomic variation in modern human populations. Several gene regions have been identified previously as candidates of adaptive introgression (AI) that facilitated human adaptation to specific environments. However, simulation-based studies have suggested that population genetic processes other than adaptive mutations, such as heterosis from recessive deleterious variants private to populations before admixture, can also lead to patterns in genomic data that resemble AI. The extent to which the presence of deleterious variants affect the false-positive rate and the power of current methods to detect AI has not been fully assessed. Here, we used extensive simulations under parameters relevant for human evolution to show that recessive deleterious mutations can increase the false positive rates of tests for AI compared to models without deleterious variants, especially when the recombination rates are low. We next examined candidates of AI in modern humans identified from previous studies, and show that 24 out of 26 candidate regions remain significant, even when deleterious variants are included in the null model. However, two AI candidate genes, HYAL2 and HLA, are particularly susceptible to high false positive signals of AI due to recessive deleterious mutations. These genes are located in regions of the human genome with high exon density together with low recombination rate, factors that we show increase the rate of false-positives due to recessive deleterious mutations. Although the combination of such parameters is rare in the human genome, caution is warranted in such regions, as well as in other species with more compact genomes and/or lower recombination rates. In sum, our results suggest that recessive deleterious mutations cannot account for the signals of AI in most, but not all, of the top candidates for AI in humans, suggesting they may be genuine signals of adaptation.

scholarly journals Deleterious variation mimics signatures of genomic incompatibility and adaptive introgression

2017 ◽  
Author(s):  
Bernard Y. Kim ◽  
Christian D. Huber ◽  
Kirk E. Lohmueller
Keyword(s):  
Population Genetic ◽  
Natural Populations ◽  
Genetic Load ◽  
Population Admixture ◽  
Population Differences ◽  
Deleterious Mutations ◽  
Recombination Rates ◽  
Adaptive Introgression ◽  
Fitness Effects ◽  
New Mutations

AbstractWhile it is appreciated that population size changes can impact patterns of deleterious variation in natural populations, less attention has been paid to how population admixture affects the dynamics of deleterious variation. Here we use population genetic simulations to examine how admixture impacts deleterious variation under a variety of demographic scenarios, dominance coefficients, and recombination rates. Our results show that gene flow between populations can temporarily reduce the genetic load of smaller populations, especially if deleterious mutations are recessive. Additionally, when fitness effects of new mutations are recessive, between-population differences in the sites at which deleterious variants exist creates heterosis in hybrid individuals. This can lead to an increase in introgressed ancestry, particularly when recombination rates are low. Under certain scenarios, introgressed ancestry can increase from an initial frequency of 5% to 30-75% and fix at many loci, even in the absence of beneficial mutations. Further, deleterious variation and admixture can generate correlations between the frequency of introgressed ancestry and recombination rate or exon density, even in the absence of other types of selection. The direction of these correlations is determined by the specific demography and whether mutations are additive or recessive. Therefore, it is essential that null models include both demography and deleterious variation before invoking reproductive incompatibilities or adaptive introgression to explain unusual patterns of genetic variation.

scholarly journals VolcanoFinder: genomic scans for adaptive introgression

2019 ◽  
Author(s):  
Derek Setter ◽  
Sylvain Mousset ◽  
Xiaoheng Cheng ◽  
Rasmus Nielsen ◽  
Michael DeGiorgio ◽  
...  
Keyword(s):  
Related Species ◽  
Genomic Data ◽  
Composite Likelihood ◽  
Genomic Variation ◽  
Human Populations ◽  
Closely Related Species ◽  
Adaptive Introgression ◽  
A Genome ◽  
Wide Range ◽  
Donor Species

AbstractRecent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method—VolcanoFinder—to detect recent events of adaptive introgression using polymorphism data from the recipient species only.VolcanoFinder detects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity.Using coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show that VolcanoFinder has high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implement VolcanoFinder to detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such as TSHR in Europeans and TCHH-RPTN in Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications of VolcanoFinder.Author summaryThe process by which beneficial alleles are introduced into a species from a closely-related species is termed adaptive introgression. We present an analytically-tractable model for the effects of adaptive introgression on non-adaptive genetic variation in the genomic region surrounding the beneficial allele. The result we describe is a characteristic volcano-shaped pattern of increased variability that arises around the positively-selected site, and we introduce an open-source method VolcanoFinder to detect this signal in genomic data. Importantly, VolcanoFinder is a population-genetic likelihood-based approach, rather than a comparative-genomic approach, and can therefore probe genomic variation data from a single population for footprints of adaptive introgression, even from a priori unknown and possibly extinct donor species.

Improving diagnosis of acute appendicitis with atypical findings by Tc-99m HMPAO leukocyte scan

2002 ◽  
Vol 41 (01) ◽  
pp. 37-41 ◽  
Author(s):  
S. Shung-Shung ◽  
S. Yu-Chien ◽  
Y. Mei-Due ◽  
W. Hwei-Chung ◽  
A. Kao
Keyword(s):  
Acute Appendicitis ◽  
False Positive ◽  
False Positive Rate ◽  
Accurate Method ◽  
Clinical Findings ◽  
Pathological Findings ◽  
Lower Quadrant ◽  
Predictive Values ◽  
Positive Rate

Summary Aim: Even with careful observation, the overall false-positive rate of laparotomy remains 10-15% when acute appendicitis was suspected. Therefore, the clinical efficacy of Tc-99m HMPAO labeled leukocyte (TC-WBC) scan for the diagnosis of acute appendicitis in patients presenting with atypical clinical findings is assessed. Patients and Methods: Eighty patients presenting with acute abdominal pain and possible acute appendicitis but atypical findings were included in this study. After intravenous injection of TC-WBC, serial anterior abdominal/pelvic images at 30, 60, 120 and 240 min with 800k counts were obtained with a gamma camera. Any abnormal localization of radioactivity in the right lower quadrant of the abdomen, equal to or greater than bone marrow activity, was considered as a positive scan. Results: 36 out of 49 patients showing positive TC-WBC scans received appendectomy. They all proved to have positive pathological findings. Five positive TC-WBC were not related to acute appendicitis, because of other pathological lesions. Eight patients were not operated and clinical follow-up after one month revealed no acute abdominal condition. Three of 31 patients with negative TC-WBC scans received appendectomy. They also presented positive pathological findings. The remaining 28 patients did not receive operations and revealed no evidence of appendicitis after at least one month of follow-up. The overall sensitivity, specificity, accuracy, positive and negative predictive values for TC-WBC scan to diagnose acute appendicitis were 92, 78, 86, 82, and 90%, respectively. Conclusion: TC-WBC scan provides a rapid and highly accurate method for the diagnosis of acute appendicitis in patients with equivocal clinical examination. It proved useful in reducing the false-positive rate of laparotomy and shortens the time necessary for clinical observation.

Predicting Fetal Chromosome Anomalies in the First Trimester Using Pregnancy Associated Plasma Protein-A: A Comparison of Statistical Methods

1993 ◽  
Vol 32 (02) ◽  
pp. 175-179 ◽  
Author(s):  
B. Brambati ◽  
T. Chard ◽  
J. G. Grudzinskas ◽  
M. C. M. Macintosh
Keyword(s):  
Logistic Regression ◽  
General Population ◽  
Likelihood Ratio ◽  
False Positive ◽  
False Positive Rate ◽  
Ratio Method ◽  
Detection Rates ◽  
Gaussian Distributions ◽  
Positive Rate ◽  
Likelihood Ratio Method

Abstract:The analysis of the clinical efficiency of a biochemical parameter in the prediction of chromosome anomalies is described, using a database of 475 cases including 30 abnormalities. A comparison was made of two different approaches to the statistical analysis: the use of Gaussian frequency distributions and likelihood ratios, and logistic regression. Both methods computed that for a 5% false-positive rate approximately 60% of anomalies are detected on the basis of maternal age and serum PAPP-A. The logistic regression analysis is appropriate where the outcome variable (chromosome anomaly) is binary and the detection rates refer to the original data only. The likelihood ratio method is used to predict the outcome in the general population. The latter method depends on the data or some transformation of the data fitting a known frequency distribution (Gaussian in this case). The precision of the predicted detection rates is limited by the small sample of abnormals (30 cases). Varying the means and standard deviations (to the limits of their 95% confidence intervals) of the fitted log Gaussian distributions resulted in a detection rate varying between 42% and 79% for a 5% false-positive rate. Thus, although the likelihood ratio method is potentially the better method in determining the usefulness of a test in the general population, larger numbers of abnormal cases are required to stabilise the means and standard deviations of the fitted log Gaussian distributions.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

Characteristics of false-positive alerts on transcranial motor evoked potential monitoring during pediatric scoliosis and adult spinal deformity surgery: an “anesthetic fade” phenomenon

2020 ◽  
Vol 32 (3) ◽  
pp. 423-431 ◽  
Author(s):  
Hiroki Ushirozako ◽  
Go Yoshida ◽  
Tomohiko Hasegawa ◽  
Yu Yamato ◽  
Tatsuya Yasuda ◽  
...  
Keyword(s):  
Spinal Deformity ◽  
False Positive ◽  
Adult Spinal Deformity ◽  
False Positive Rate ◽  
Multivariate Logistic Regression Analysis ◽  
Motor Evoked Potential ◽  
Scoliosis Surgery ◽  
True Negative ◽  
Duration Of Surgery ◽  
Spinal Deformity Surgery

OBJECTIVETranscranial motor evoked potential (TcMEP) monitoring may be valuable for predicting postoperative neurological complications with a high sensitivity and specificity, but one of the most frequent problems is the high false-positive rate. The purpose of this study was to clarify the differences in the risk factors for false-positive TcMEP alerts seen when performing surgery in patients with pediatric scoliosis and adult spinal deformity and to identify a method to reduce the false-positive rate.METHODSThe authors retrospectively analyzed 393 patients (282 adult and 111 pediatric patients) who underwent TcMEP monitoring while under total intravenous anesthesia during spinal deformity surgery. They defined their cutoff (alert) point as a final TcMEP amplitude of ≤ 30% of the baseline amplitude. Patients with false-positive alerts were classified into one of two groups: a group with pediatric scoliosis and a group with adult spinal deformity.RESULTSThere were 14 cases of false-positive alerts (13%) during pediatric scoliosis surgery and 62 cases of false-positive alerts (22%) during adult spinal deformity surgery. Compared to the true-negative cases during adult spinal deformity surgery, the false-positive cases had a significantly longer duration of surgery and greater estimated blood loss (both p < 0.001). Compared to the true-negative cases during pediatric scoliosis surgery, the false-positive cases had received a significantly higher total fentanyl dose and a higher mean propofol dose (0.75 ± 0.32 mg vs 0.51 ± 0.18 mg [p = 0.014] and 5.6 ± 0.8 mg/kg/hr vs 5.0 ± 0.7 mg/kg/hr [p = 0.009], respectively). A multivariate logistic regression analysis revealed that the duration of surgery (1-hour difference: OR 1.701; 95% CI 1.364–2.120; p < 0.001) was independently associated with false-positive alerts during adult spinal deformity surgery. A multivariate logistic regression analysis revealed that the mean propofol dose (1-mg/kg/hr difference: OR 3.117; 95% CI 1.196–8.123; p = 0.020), the total fentanyl dose (0.05-mg difference; OR 1.270; 95% CI 1.078–1.497; p = 0.004), and the duration of surgery (1-hour difference: OR 2.685; 95% CI 1.131–6.377; p = 0.025) were independently associated with false-positive alerts during pediatric scoliosis surgery.CONCLUSIONSLonger duration of surgery and greater blood loss are more likely to result in false-positive alerts during adult spinal deformity surgery. In particular, anesthetic doses were associated with false-positive TcMEP alerts during pediatric scoliosis surgery. The authors believe that false-positive alerts during pediatric scoliosis surgery, in particular, are caused by “anesthetic fade.”

scholarly journals PRATD: A Phased Remote Access Trojan Detection Method with Double-Sided Features

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1894
Author(s):  
Chun Guo ◽  
Zihua Song ◽  
Yuan Ping ◽  
Guowei Shen ◽  
Yuhei Cui ◽  
...  
Keyword(s):  
False Positive ◽  
Detection Method ◽  
False Positive Rate ◽  
True Positive Rate ◽  
Remote Access ◽  
Detection Methods ◽  
Security Threats ◽  
True Positive ◽  
Trojan Detection ◽  
Positive Rate

Remote Access Trojan (RAT) is one of the most terrible security threats that organizations face today. At present, two major RAT detection methods are host-based and network-based detection methods. To complement one another’s strengths, this article proposes a phased RATs detection method by combining double-side features (PRATD). In PRATD, both host-side and network-side features are combined to build detection models, which is conducive to distinguishing the RATs from benign programs because that the RATs not only generate traffic on the network but also leave traces on the host at run time. Besides, PRATD trains two different detection models for the two runtime states of RATs for improving the True Positive Rate (TPR). The experiments on the network and host records collected from five kinds of benign programs and 20 famous RATs show that PRATD can effectively detect RATs, it can achieve a TPR as high as 93.609% with a False Positive Rate (FPR) as low as 0.407% for the known RATs, a TPR 81.928% and FPR 0.185% for the unknown RATs, which suggests it is a competitive candidate for RAT detection.

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