Ancestry Informative Marker Panel to Estimate Population Stratification Using Genome-wide Human Array

2017 ◽  
Vol 81 (6) ◽  
pp. 225-233 ◽  
Author(s):  
Fernanda B. Barbosa ◽  
Natalia F. Cagnin ◽  
Milena Simioni ◽  
Allysson A. Farias ◽  
Fábio R. Torres ◽  
...  
Keyword(s):  
Population Stratification ◽  
Ancestry Informative Marker ◽  
Informative Marker ◽  
Marker Panel ◽  
Genome Wide

1-OR: HLA as an ancestry informative marker (AIM)

2007 ◽  
Vol 68 (1) ◽  
pp. S9
Author(s):  
Loren Gragert ◽  
Martin Maiers ◽  
William Klitz
Keyword(s):  
Ancestry Informative Marker ◽  
Informative Marker

scholarly journals A practical approach to adjusting for population stratification in genome-wide association studies: principal components and propensity scores (PCAPS)

2018 ◽  
Vol 17 (6) ◽  
Author(s):  
Huaqing Zhao ◽  
Nandita Mitra ◽  
Peter A. Kanetsky ◽  
Katherine L. Nathanson ◽  
Timothy R. Rebbeck
Keyword(s):  
Principal Components ◽  
Population Stratification ◽  
Propensity Scores ◽  
Association Studies ◽  
Germ Cell Tumors ◽  
Gwas Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Testicular Germ Cell ◽  
Genome Wide

Abstract Genome-wide association studies (GWAS) are susceptible to bias due to population stratification (PS). The most widely used method to correct bias due to PS is principal components (PCs) analysis (PCA), but there is no objective method to guide which PCs to include as covariates. Often, the ten PCs with the highest eigenvalues are included to adjust for PS. This selection is arbitrary, and patterns of local linkage disequilibrium may affect PCA corrections. To address these limitations, we estimate genomic propensity scores based on all statistically significant PCs selected by the Tracy-Widom (TW) statistic. We compare a principal components and propensity scores (PCAPS) approach to PCA and EMMAX using simulated GWAS data under no, moderate, and severe PS. PCAPS reduced spurious genetic associations regardless of the degree of PS, resulting in odds ratio (OR) estimates closer to the true OR. We illustrate our PCAPS method using GWAS data from a study of testicular germ cell tumors. PCAPS provided a more conservative adjustment than PCA. Advantages of the PCAPS approach include reduction of bias compared to PCA, consistent selection of propensity scores to adjust for PS, the potential ability to handle outliers, and ease of implementation using existing software packages.

scholarly journals Microhaplotype: Ability of personal identification and being ancestry informative marker

2017 ◽  
Vol 6 ◽  
pp. e442-e444 ◽  
Author(s):  
Yan Pu ◽  
Peng Chen ◽  
Jing Zhu ◽  
Youjing Jiang ◽  
Qingqing Li ◽  
...  
Keyword(s):  
Personal Identification ◽  
Ancestry Informative Marker ◽  
Informative Marker

scholarly journals Copy Number Alterations of Depressed Colorectal Neoplasm Predict the Survival and Response to Oxaliplatin in Proximal Colon Cancer

Cancers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1527
Author(s):  
Li-Chun Chang ◽  
Han-Mo Chiu ◽  
Bing-Ching Ho ◽  
Min-Hsuan Chen ◽  
Yin-Chen Hsu ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Copy Number ◽  
Colorectal Neoplasm ◽  
Progression Free Survival ◽  
Proximal Colon ◽  
Copy Number Alterations ◽  
Free Survival ◽  
Marker Panel ◽  
Genome Wide ◽  
Prospective Trials

Depressed colorectal neoplasm exhibits high malignant potential and shows rapid invasiveness. We investigated the genomic profile of depressed neoplasms and clarified the survival outcome and treatment response of the cancers arising from them. We examined 20 depressed and 13 polypoid neoplasms by genome-wide copy number analysis. Subsequently, we validated the identified copy number alterations (CNAs) in an independent cohort of 37 depressed and 42 polypoid neoplasms. Finally, the CNAs were tested as biomarkers in 530 colorectal cancers (CRCs) to clarify the clinical outcome of depressed neoplasms. CNAs in MYC, CCNA1, and BIRC7 were significantly enriched in depressed neoplasms and designated as the D-marker panel. CRCs with a D-marker panel have significantly shorter progression-free survival compared with those without (p = 0.012), especially in stage I (p = 0.049), stages T1+2 (p = 0.027), and proximal cancers (p = 0.002). The positivity of the D-marker panel was an independent risk factor of cancer progression (hazard ratio (95% confidence interval) = 1.52 (1.09–2.11)). Furthermore, the proximal CRCs with D-marker panels had worse overall and progression-free survival when taking oxaliplatin as chemotherapy than those that did not. The D-marker panel may help to optimize treatment and surveillance in proximal CRC and develop a molecular test. However, the current result remains preliminary, and further validation in prospective trials is warranted in the future.

Genomic determinants of prognosis in esophageal adenocarcinoma: Using computational methods to account for gene-gene interactions.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 42-42
Author(s):  
Eric Morgen ◽  
Xiaowei Shen ◽  
Thomas L. Vaughan ◽  
David Whiteman ◽  
Anna H. Wu ◽  
...  
Keyword(s):  
Quality Control ◽  
Esophageal Adenocarcinoma ◽  
Population Stratification ◽  
Cox Proportional Hazards ◽  
Interactive Effects ◽  
Gene Interactions ◽  
P Value ◽  
Tumor Resistance ◽  
Genome Wide ◽  
A Genome

42 Background: Methods of stratifying esophageal adenocarcinoma patients into prognostic groups are needed, as are new insights into genetic determinants of disease behaviour. Prognosis is likely to have non-negligible genetic influences, as mediated by host responses to tumor, resistance to therapeutic side-effects, and/or an influence on tumor development. Prior studies have used candidate-gene approaches. We took an alternative approach, using an unbiased, genome-wide approach, and novel analytic methods that may be better able to detect multi-gene interactions, which may contribute the majority of genetic effects for many clinical phenotypes. Methods: Germline DNA from a Toronto-based cohort of EAC patients (n=270) was analyzed by Omni1 Quad microarray as part of the BEAGESS initiative. Quality control and analysis was performed using PLINK, R, and GenABEL software packages. A Cox proportional hazards (CPH) model for progression-free survival tested each polymorphism for independent effects at a genome-wide significance level of P < 1E-07, adjusting for population stratification. While classical analysis has limited ability to detect gene-gene interactions, a Random Survival Forest algorithm was used to detect effects based on the complex interactions among top 1,000 polymorphisms by p-value ranking. Results: After data cleaning and standard GWAS quality control procedures, there were 735,309 SNPs and 245 patients remaining for analysis. The CPH model, adjusted for population stratification, produced a satisfactory Q-Q plot, and showed one SNP (rs7844673, Chr 8) that was significant at p=7.8E-8. In addition, Random Forest based variable selection produced a set of 20 polymorphisms that (1) reproduced 86% of the predictive ability of the full 1000 variables, and (2) also included the #3 ranked polymorphism by CPH modeling (rs9290822, Chr 3) upstream of the IGF2BP2 gene. Conclusions: A genome-wide approach has discovered two previously undescribed SNPs with a potential influence on EAC prognosis via a combination of independent and interactive effects. Validation in an independent cohort is currently being pursued.

scholarly journals Identification of novel candidate genes for the inverted teat defect in sows using a genome-wide marker panel

2017 ◽  
Vol 58 (2) ◽  
pp. 249-259
Author(s):  
Helena Chalkias ◽  
Elisabeth Jonas ◽  
Lisa S. Andersson ◽  
Magdalena Jacobson ◽  
Dirk Jan de Koning ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Marker Panel ◽  
Genome Wide ◽  
A Genome
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