Implications Of Mixed Results With Cointegration Models In International Studies

While cointegration models have been used extensively in many fields (such as in testing for stock market predictability), there have been mixed results from using cointegration models in international studies.  For example, one study attempted to regress the levels of the general stock market price indexes of Norway, Mexico, Venezuela, and of Oman on the levels of interest rate and oil prices variables during the period 1992 to 1999.  Attempts to explain mixed results have included distinguishing developed markets versus less developed markets and differences in the volatilities of markets. Another approach has been attempts to improve cointegration methods.  Some studies have included both bivariate and multivariate methods of cointegration.  Others have employed augmented Dickey-Fuller unit root tests of the residuals.  The extent of mixed results in international studies has implications for earlier studies in single countries.  It is possible that many earlier studies in business and in economics will need to be replicated using newer techniques developed by international researchers.  The purpose of this study is to explain the attempts to improve cointegration methods, the mixed results in international studies, and the implications for earlier studies relying upon cointegration models

Recurrent miscalling of missense variation from short-read genome sequence data

Background: Short-read resequencing of genomes produces abundant information of the genetic variation of individuals. Due to their numerous nature, these variants are rarely exhaustively validated. Furthermore, low levels of undetected variant miscalling will have a systematic and disproportionate impact on the interpretation of individual genome sequence information, especially should these also be carried through into in reference databases ofgenomic variation. Results: We find that sequence variation from short-read sequence data is subject to recurrent-yet-intermittent miscalling that occurs in a sequence intrinsic manner and is very sensitive to sequence read length. The miscalls arise from difficulties aligning short reads to redundant genomic regions, where the rate of sequencing error approaches the sequence diversity between redundant regions. We find the resultant miscalled variants to be sensitive to small sequence variations between genomes, and thereby are often intrinsic to an individual, pedigree, strain or human ethnic group. In human exome sequences, we identify 2–300 recurrent false positive variants per individual, almost all of which are present in public databases of human genomic variation. From the exomes of non-reference strains of inbred mice, we identify 3–5000 recurrent false positive variants per mouse – the number of which increasing with greater distance between an individual mouse strain and the reference C57BL6 mouse genome. We show that recurrently miscalled variants may be reproduced for a given genome from repeated simulation rounds of read resampling, realignment and recalling. As such, it is possible to identify more than two-thirds of false positive variation from only ten rounds of simulation. Conclusion: Identification and removal of recurrent false positive variants from specific individual variant sets will improve overall data quality. Variant miscalls arising are highly sequence intrinsic and are often specific to an individual, pedigree or ethnicity. Further, read length is a strong determinant of whether given false variants will be called for any given genome – which has profound significance for cohort studies that pool datasets collected and sequenced at different points in time

Recurrent miscalling of missense variation from short-read genome sequence data

Background Short-read resequencing of genomes produces abundant information of the genetic variation of individuals. Due to their numerous nature, these variants are rarely exhaustively validated. Furthermore, low levels of undetected variant miscalling will have a systematic and disproportionate impact on the interpretation of individual genome sequence information, especially should these also be carried through into in reference databases of genomic variation. Results We find that sequence variation from short-read sequence data is subject to recurrent-yet-intermittent miscalling that occurs in a sequence intrinsic manner and is very sensitive to sequence read length. The miscalls arise from difficulties aligning short reads to redundant genomic regions, where the rate of sequencing error approaches the sequence diversity between redundant regions. We find the resultant miscalled variants to be sensitive to small sequence variations between genomes, and thereby are often intrinsic to an individual, pedigree, strain or human ethnic group. In human exome sequences, we identify 2–300 recurrent false positive variants per individual, almost all of which are present in public databases of human genomic variation. From the exomes of non-reference strains of inbred mice, we identify 3–5000 recurrent false positive variants per mouse – the number of which increasing with greater distance between an individual mouse strain and the reference C57BL6 mouse genome. We show that recurrently miscalled variants may be reproduced for a given genome from repeated simulation rounds of read resampling, realignment and recalling. As such, it is possible to identify more than two-thirds of false positive variation from only ten rounds of simulation. Conclusion Identification and removal of recurrent false positive variants from specific individual variant sets will improve overall data quality. Variant miscalls arising are highly sequence intrinsic and are often specific to an individual, pedigree or ethnicity. Further, read length is a strong determinant of whether given false variants will be called for any given genome – which has profound significance for cohort studies that pool datasets collected and sequenced at different points in time.This work has been funded by National Institutes of Health Grant AI100627 and the National Collaborative Research Infrastructure Strategy (Australia). Publication costs are funded by National Institutes of Health Grant AI100627 and the National Collaborative Research Infrastructure Strategy (Australia)

Geographic range did not confer resilience to extinction in terrestrial vertebrates at the end-Triassic crisis

Rates of extinction vary greatly through geological time, with losses particularly concentrated in mass extinctions. Species duration at other times varies greatly, but the reasons for this are unclear. Geographical range correlates with lineage duration amongst marine invertebrates, but it is less clear how far this generality extends to other groups in other habitats. It is also unclear whether a wide geographical distribution makes groups more likely to survive mass extinctions. Here we test for extinction selectivity amongst terrestrial vertebrates across the end-Triassic event. We demonstrate that terrestrial vertebrate clades with larger geographical ranges were more resilient to extinction than those with smaller ranges throughout the Triassic and Jurassic. However, this relationship weakened with increasing proximity to the end-Triassic mass extinction, breaking down altogether across the event itself. We demonstrate that these findings are not a function of sampling biases; a perennial issue in studies of this kind

Calcitization of aragonitic bryozoans in Cenozoic tropical carbonates from East Kalimantan, Indonesia

© The Author(s) 2016. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The file attached is the published version of the article

Cost-effectiveness of public health strategies for COVID-19 epidemic control in South Africa

Background Healthcare resource constraints in low and middle-income countries necessitate selection of cost-effective public health interventions to address COVID-19. Methods We developed a dynamic COVID-19 microsimulation model to evaluate clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal, South Africa. Interventions assessed were Healthcare Testing (HT), where diagnostic testing is performed only for those presenting to healthcare centres; Contact Tracing (CT) in households of cases; Isolation Centres (IC), for cases not requiring hospitalisation; community health worker-led Mass Symptom Screening and diagnostic testing for symptomatic individuals (MS); and Quarantine Centres (QC), for contacts who test negative. Given uncertainties about epidemic dynamics in South Africa, we evaluated two main epidemic scenarios over 360 days, with effective reproduction numbers (R e ) of 1.5 and 1.2. We compared HT, HT+CT, HT+CT+IC, HT+CT+IC+MS, HT+CT+IC+QC, and HT+CT+IC+MS+QC, considering strategies with incremental cost-effectiveness ratio (ICER) <US$1,290/year-of-life saved (YLS) to be cost-effective. Findings With R e 1.5, HT resulted in the most COVID-19 deaths and lowest costs over 360 days. Compared with HT, HT+CT+IC+MS reduced mortality by 76$350/YLS). HT+CT+IC+MS+QC provided the greatest reduction in mortality, but increased costs by 95% compared with HT+CT+IC+MS and was not cost-effective (ICER $8,000/YLS). With R e 1.2, HT+CT+IC+MS was the least costly strategy, and HT+CT+IC+MS+QC was not cost-effective (ICER$294,320/YLS). Interpretation In South Africa, a strategy of household contact tracing, isolation, and mass symptom screening would substantially reduce COVID-19 mortality and be cost-effective. Adding quarantine centres for COVID-19 contacts is not cost-effective