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Research Articles
Jacqueline A. Merrill, Mark Orr, Daniel Y. Chen, Qi Zhi, Robyn R. Gershon
Disaster Medicine and Public Health Preparedness, FirstView Article(s), 11 pages
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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When genome-wide association studies (GWAS) or sequencing studies are performed on family-based datasets, the genotype data can be used to check the structure of putative pedigrees. Even in datasets of putatively unrelated people, close relationships can often be detected using dense single-nucleotide polymorphism/variant (SNP/SNV) data. A number of methods for finding relationships using dense genetic data exist, but they all have certain limitations, including that they typically use average genetic sharing, which is only a subset of the available information. Here, we present a set of approaches for classifying relationships in GWAS datasets or large-scale sequencing datasets. We first propose an empirical method for detecting identity by descent segments in close relative pairs using un-phased dense SNP data and demonstrate how that information can assist in building a relationship classifier. We then develop a strategy to take advantage of putative pedigree information to enhance classification accuracy. Our methods are tested and illustrated with two datasets from two distinct populations. Finally, we propose classification pipelines for checking and identifying relationships in datasets containing a large number of small pedigrees.
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Genome-wide association studies are proven tools for finding disease genes, but it is often necessary to combine many cohorts into a meta-analysis to detect statistically significant genetic effects. Often the component studies are performed by different investigators on different populations, using different chips with minimal SNPs overlap. In some cases, raw data are not available for imputation so that only the genotyped single nucleotide polymorphisms (SNPs) results can be used in meta-analysis. Even when SNP sets are comparable, different cohorts may have peak association signals at different SNPs within the same gene due to population differences in linkage disequilibrium or environmental interactions. We hypothesize that the power to detect statistical signals in these situations will improve by using a method that simultaneously meta-analyzes and smooths the signal over nearby markers. In this study, we propose regionally smoothed meta-analysis methods and compare their performance on real and simulated data.
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Research Articles
S Bola, R Marsh, S Braggins, C Potter, S Hickey
The Journal of Laryngology Otology, FirstView Article(s), 5 pages
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With a typical sample size of a few thousand subjects, a single genome-wide association study (GWAS) using traditional one single nucleotide polymorphism (SNP)-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. Although self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly "adapt" to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a least absolute shrinkage and selection operator (LASSO)-based test.
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Invasive Candida spp. infections are increasingly diagnosed in critically ill patients. For initial treatment, an echinocandin is recommended with a possible step-down to fluconazole when the patients' condition is improving and the isolate appears susceptible, but there are no data to support such policy. We studied the safety and efficacy of step-down therapy in critically ill patients with culture proven deep seated or bloodstream infections by C. albicans susceptible to fluconazole. All patients admitted into the intensive care unit from January 2010 to December 2014, who had a culture proven invasive C. albicans infection and received initial treatment with an echinocandin for at least 4 days were included. Data on patient characteristics, treatment and vital outcomes were assessed. Of the 56 patients, 32 received step-down fluconazole therapy, at median day 5, whereas the echinocandin was continued in the other 24. No differences where seen in baseline characteristics or risk factors for invasive C. albicans infection between the two groups. Response rates were similar and no difference where seen in 28-day or 90-day mortality between the groups. Step-down therapy to fluconazole may be safe and effective in critically ill patients with invasive infections by C. albicans, susceptible to fluconazole, who have clinically improved as early as 4 days after start of treatment with an echinocandin.
Invasive Candida spp. infections are increasingly diagnosed in critically ill patients. For initial treatment, an echinocandin is recommended with a possible step-down to fluconazole when the patients' condition is improving and the isolate appears susceptible, but there are no data to support such policy. We studied the safety and efficacy of step-down therapy in critically ill patients with culture proven deep seated or bloodstream infections by C. albicans susceptible to fluconazole. All patients admitted into the intensive care unit from January 2010 to December 2014, who had a culture proven invasive C. albicans infection and received initial treatment with an echinocandin for at least 4 days were included. Data on patient characteristics, treatment and vital outcomes were assessed. Of the 56 patients, 32 received step-down fluconazole therapy, at median day 5, whereas the echinocandin was continued in the other 24. No differences where seen in baseline characteristics or risk factors for invasive C. albicans infection between the two groups. Response rates were similar and no difference where seen in 28-day or 90-day mortality between the groups. Step-down therapy to fluconazole may be safe and effective in critically ill patients with invasive infections by C. albicans, susceptible to fluconazole, who have clinically improved as early as 4 days after start of treatment with an echinocandin.
Research Articles
M Dhiwakar, G I Nambi, T V Ramanikanth, S M Kale, M N Sivakumar
The Journal of Laryngology Otology, FirstView Article(s), 5 pages
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Research Articles
S Bola, R Marsh, S Braggins, C Potter, S Hickey
The Journal of Laryngology Otology, FirstView Article(s), 5 pages
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The aim of this study was to evaluate whether the adjunctive use of a collagen membrane enhances bone formation and implant osseointegration in non-contained defects grafted with chair-side prepared autologous platelet-rich growth factor (PRGF) adsorbed on a β-TCP particulate carrier.
Large box-type defects (10 × 6 mm; W × D) were prepared in the edentulated and completely healed mandibles of six Beagles dogs. An implant with moderately rough surface was placed in the center of each defect leaving the coronal 6 mm of the implant not covered with bone. The remaining defect space was then filled out with chair-side prepared autologous PRGF adsorbed on β-TCP particles and either covered with a collagen membrane (PRGF/β-TCP+CM) (6 defects) or left without a membrane (PRGF/β-TCP) (5 defects).
Histology 4 months post-op showed new lamellar and woven bone formation encompassing almost entirely the defect and limited residual β-TCP particles. Extent of osseointegration of the previously exposed portion of the implants varied, but in general was limited. Within the defect, new mineralized bone (%) averaged 43.2 ± 9.86 vs. 39.9 ± 13.7 in the PRGF/β-TCP+CM and PRGF/β-TCP group (P = 0.22) and relative mineralized bone-to-implant contact (%) averaged 26.2 ± 16.45 vs. 35.91 ± 24.45, respectively (P = 0.5). First, bone-to-implant contact from the implant top was 4.1 ± 1.5 and 3.2 ± 2.3 (P = 0.9), in the PRGF/β-TCP+CM and PRGF/β-TCP group, respectively.
Implantation of chair-side prepared autologous PRGF adsorbed on a β-TCP carrier in non-contained peri-implant defects resulted in large amounts of bone regeneration, but osseointegration was limited. Provisions for GBR with a collagen membrane did not significantly enhance bone regeneration or implant osseointegration.
The aim of this study was to evaluate whether the adjunctive use of a collagen membrane enhances bone formation and implant osseointegration in non-contained defects grafted with chair-side prepared autologous platelet-rich growth factor (PRGF) adsorbed on a β-TCP particulate carrier.
Large box-type defects (10 × 6 mm; W × D) were prepared in the edentulated and completely healed mandibles of six Beagles dogs. An implant with moderately rough surface was placed in the center of each defect leaving the coronal 6 mm of the implant not covered with bone. The remaining defect space was then filled out with chair-side prepared autologous PRGF adsorbed on β-TCP particles and either covered with a collagen membrane (PRGF/β-TCP+CM) (6 defects) or left without a membrane (PRGF/β-TCP) (5 defects).
Histology 4 months post-op showed new lamellar and woven bone formation encompassing almost entirely the defect and limited residual β-TCP particles. Extent of osseointegration of the previously exposed portion of the implants varied, but in general was limited. Within the defect, new mineralized bone (%) averaged 43.2 ± 9.86 vs. 39.9 ± 13.7 in the PRGF/β-TCP+CM and PRGF/β-TCP group (P = 0.22) and relative mineralized bone-to-implant contact (%) averaged 26.2 ± 16.45 vs. 35.91 ± 24.45, respectively (P = 0.5). First, bone-to-implant contact from the implant top was 4.1 ± 1.5 and 3.2 ± 2.3 (P = 0.9), in the PRGF/β-TCP+CM and PRGF/β-TCP group, respectively.
Implantation of chair-side prepared autologous PRGF adsorbed on a β-TCP carrier in non-contained peri-implant defects resulted in large amounts of bone regeneration, but osseointegration was limited. Provisions for GBR with a collagen membrane did not significantly enhance bone regeneration or implant osseointegration.
This article focuses on the hiring trends of academic general otolaryngology practices to clarify the status of academic general otolaryngology in the face of today's changing medical landscape.
Cross-sectional study.
We conducted a survey to evaluate past, present, and projected hiring issues in academic otolaryngology, specifically related to general otolaryngology. Surveys were sent via e-mail to all academic chairpersons of accredited otolaryngology residency programs in the United States. Data included faculty appointments, work hours, clinical and research roles, academic productivity, patient load, promotions, and criteria for future hires.
The response rate was 34.3%. On average, general otolaryngologists (generalists) represented 17% of otolaryngology faculty in academic practices. Whereas most generalists were employed as assistant professors (65%), nearly half of promotions in recent years were given to generalists (49%). Between 2009 and 2014, there was an average of six new hires per academic otolaryngology practice (range: 1–13); of these new hires, 21% were generalists. Chairpersons estimated that in the next 5 years they would hire an average of three new otolaryngologists per practice (range: 0–7), of whom 39% would be generalists. Although 82% of chairpersons reported an increase in subspecialty hires, 94% reported that they would also require the same or increasing numbers of generalists.
Despite the increase in subspecialization in academic otolaryngology, the role of general otolaryngologists in academic practices will continue to be important and perhaps will increase.
N/A. Laryngoscope, 2015
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Determine predictors of high-risk and low-risk oral HPV infection in the United States.
Retrospective analyses of National Health and Nutrition Examination Survey cross-sectional data of U.S. population from 2009 to 2012.
Database queried for subjects aged 18 to 69 with oral rinse human papillomavirus (HPV) DNA data. Logistic regression identified factors associated with high-risk and low-risk infection. Covariates included age, gender, ethnicity, income-to-poverty (IP) ratio, sexual orientation, human immunodeficiency virus infection, other sexually transmitted infections, lifetime sexual partners, and lifetime oral sex partners.
In total, 9,256 subjects were identified with mean age of 42.1 years. Oral HPV infection was present in 8.1% (N = 747); 55.7% were high-risk and 55.3% were low-risk types, including 11% with both. Oral infection had a negative association with female gender (odds ratio [OR] 0.3, P < 0.001), IP ratio ≥ 3 (OR 0.7, P = 0.02), and one lifetime oral sex partner (OR 0.7, P = 0.03). Increasing oral sex behavior (6–21+ lifetime partners) was positively associated with oral HPV (OR 1.4–3.0, P = 0.03). Low-risk infection had negative associations with female gender (OR 0.4, P < 0.001) and non-Hispanic white ethnicity (OR 0.6, P = 0.02), IP ratio ≥ 3 (OR 0.6, P = 0.01), and positive association with > 20 sexual partners (all sex OR 1.7, P = 0.04; oral sex OR 1.9, P = 0.02). Predictors of high-risk HPV infection included male gender and increasing oral sex partners.
Increasing oral sex partners is positively associated with oral HPV infection; female sex and higher socioeconomic class are negatively associated. The risk-factor profiles for high-risk and low-risk HPV types are distinct, with similar trends related to sexual behaviors.
4. Laryngoscope, 2015
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Research Articles
Jacqueline A. Merrill, Mark Orr, Daniel Y. Chen, Qi Zhi, Robyn R. Gershon
Disaster Medicine and Public Health Preparedness, FirstView Article(s), 11 pages
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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When genome-wide association studies (GWAS) or sequencing studies are performed on family-based datasets, the genotype data can be used to check the structure of putative pedigrees. Even in datasets of putatively unrelated people, close relationships can often be detected using dense single-nucleotide polymorphism/variant (SNP/SNV) data. A number of methods for finding relationships using dense genetic data exist, but they all have certain limitations, including that they typically use average genetic sharing, which is only a subset of the available information. Here, we present a set of approaches for classifying relationships in GWAS datasets or large-scale sequencing datasets. We first propose an empirical method for detecting identity by descent segments in close relative pairs using un-phased dense SNP data and demonstrate how that information can assist in building a relationship classifier. We then develop a strategy to take advantage of putative pedigree information to enhance classification accuracy. Our methods are tested and illustrated with two datasets from two distinct populations. Finally, we propose classification pipelines for checking and identifying relationships in datasets containing a large number of small pedigrees.
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Genome-wide association studies are proven tools for finding disease genes, but it is often necessary to combine many cohorts into a meta-analysis to detect statistically significant genetic effects. Often the component studies are performed by different investigators on different populations, using different chips with minimal SNPs overlap. In some cases, raw data are not available for imputation so that only the genotyped single nucleotide polymorphisms (SNPs) results can be used in meta-analysis. Even when SNP sets are comparable, different cohorts may have peak association signals at different SNPs within the same gene due to population differences in linkage disequilibrium or environmental interactions. We hypothesize that the power to detect statistical signals in these situations will improve by using a method that simultaneously meta-analyzes and smooths the signal over nearby markers. In this study, we propose regionally smoothed meta-analysis methods and compare their performance on real and simulated data.
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Research Articles
S Bola, R Marsh, S Braggins, C Potter, S Hickey
The Journal of Laryngology Otology, FirstView Article(s), 5 pages
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With a typical sample size of a few thousand subjects, a single genome-wide association study (GWAS) using traditional one single nucleotide polymorphism (SNP)-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. Although self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly "adapt" to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a least absolute shrinkage and selection operator (LASSO)-based test.
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Research Articles
M Dhiwakar, G I Nambi, T V Ramanikanth, S M Kale, M N Sivakumar
The Journal of Laryngology Otology, FirstView Article(s), 5 pages
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This review describes the classification and misclassification of syndromes producing epidermal necrolysis, identifying priorities and challenges in their understanding and management. The British Journal of Dermatology (Source: Medscape Allergy Headlines)
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This article focuses on the hiring trends of academic general otolaryngology practices to clarify the status of academic general otolaryngology in the face of today's changing medical landscape.
Cross-sectional study.
We conducted a survey to evaluate past, present, and projected hiring issues in academic otolaryngology, specifically related to general otolaryngology. Surveys were sent via e-mail to all academic chairpersons of accredited otolaryngology residency programs in the United States. Data included faculty appointments, work hours, clinical and research roles, academic productivity, patient load, promotions, and criteria for future hires.
The response rate was 34.3%. On average, general otolaryngologists (generalists) represented 17% of otolaryngology faculty in academic practices. Whereas most generalists were employed as assistant professors (65%), nearly half of promotions in recent years were given to generalists (49%). Between 2009 and 2014, there was an average of six new hires per academic otolaryngology practice (range: 1–13); of these new hires, 21% were generalists. Chairpersons estimated that in the next 5 years they would hire an average of three new otolaryngologists per practice (range: 0–7), of whom 39% would be generalists. Although 82% of chairpersons reported an increase in subspecialty hires, 94% reported that they would also require the same or increasing numbers of generalists.
Despite the increase in subspecialization in academic otolaryngology, the role of general otolaryngologists in academic practices will continue to be important and perhaps will increase.
N/A. Laryngoscope, 2015
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Determine predictors of high-risk and low-risk oral HPV infection in the United States.
Retrospective analyses of National Health and Nutrition Examination Survey cross-sectional data of U.S. population from 2009 to 2012.
Database queried for subjects aged 18 to 69 with oral rinse human papillomavirus (HPV) DNA data. Logistic regression identified factors associated with high-risk and low-risk infection. Covariates included age, gender, ethnicity, income-to-poverty (IP) ratio, sexual orientation, human immunodeficiency virus infection, other sexually transmitted infections, lifetime sexual partners, and lifetime oral sex partners.
In total, 9,256 subjects were identified with mean age of 42.1 years. Oral HPV infection was present in 8.1% (N = 747); 55.7% were high-risk and 55.3% were low-risk types, including 11% with both. Oral infection had a negative association with female gender (odds ratio [OR] 0.3, P < 0.001), IP ratio ≥ 3 (OR 0.7, P = 0.02), and one lifetime oral sex partner (OR 0.7, P = 0.03). Increasing oral sex behavior (6–21+ lifetime partners) was positively associated with oral HPV (OR 1.4–3.0, P = 0.03). Low-risk infection had negative associations with female gender (OR 0.4, P < 0.001) and non-Hispanic white ethnicity (OR 0.6, P = 0.02), IP ratio ≥ 3 (OR 0.6, P = 0.01), and positive association with > 20 sexual partners (all sex OR 1.7, P = 0.04; oral sex OR 1.9, P = 0.02). Predictors of high-risk HPV infection included male gender and increasing oral sex partners.
Increasing oral sex partners is positively associated with oral HPV infection; female sex and higher socioeconomic class are negatively associated. The risk-factor profiles for high-risk and low-risk HPV types are distinct, with similar trends related to sexual behaviors.
4. Laryngoscope, 2015
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Research Articles
Jacqueline A. Merrill, Mark Orr, Daniel Y. Chen, Qi Zhi, Robyn R. Gershon
Disaster Medicine and Public Health Preparedness, FirstView Article(s), 11 pages
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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This article is protected by copyright. All rights reserved. (Source: Scandinavian Journal of Immunology)
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When genome-wide association studies (GWAS) or sequencing studies are performed on family-based datasets, the genotype data can be used to check the structure of putative pedigrees. Even in datasets of putatively unrelated people, close relationships can often be detected using dense single-nucleotide polymorphism/variant (SNP/SNV) data. A number of methods for finding relationships using dense genetic data exist, but they all have certain limitations, including that they typically use average genetic sharing, which is only a subset of the available information. Here, we present a set of approaches for classifying relationships in GWAS datasets or large-scale sequencing datasets. We first propose an empirical method for detecting identity by descent segments in close relative pairs using un-phased dense SNP data and demonstrate how that information can assist in building a relationship classifier. We then develop a strategy to take advantage of putative pedigree information to enhance classification accuracy. Our methods are tested and illustrated with two datasets from two distinct populations. Finally, we propose classification pipelines for checking and identifying relationships in datasets containing a large number of small pedigrees.
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Genome-wide association studies are proven tools for finding disease genes, but it is often necessary to combine many cohorts into a meta-analysis to detect statistically significant genetic effects. Often the component studies are performed by different investigators on different populations, using different chips with minimal SNPs overlap. In some cases, raw data are not available for imputation so that only the genotyped single nucleotide polymorphisms (SNPs) results can be used in meta-analysis. Even when SNP sets are comparable, different cohorts may have peak association signals at different SNPs within the same gene due to population differences in linkage disequilibrium or environmental interactions. We hypothesize that the power to detect statistical signals in these situations will improve by using a method that simultaneously meta-analyzes and smooths the signal over nearby markers. In this study, we propose regionally smoothed meta-analysis methods and compare their performance on real and simulated data.
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Research Articles
S Bola, R Marsh, S Braggins, C Potter, S Hickey
The Journal of Laryngology Otology, FirstView Article(s), 5 pages
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With a typical sample size of a few thousand subjects, a single genome-wide association study (GWAS) using traditional one single nucleotide polymorphism (SNP)-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. Although self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly "adapt" to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a least absolute shrinkage and selection operator (LASSO)-based test.
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Research Articles
M Dhiwakar, G I Nambi, T V Ramanikanth, S M Kale, M N Sivakumar
The Journal of Laryngology Otology, FirstView Article(s), 5 pages
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