about
High-density genotyping of immune-related loci identifies new SLE risk variants in individuals with Asian ancestryA genome-wide association study of chronic obstructive pulmonary disease in Hispanics.DISSCO: direct imputation of summary statistics allowing covariatesSingle Nucleotide Polymorphism (SNP) Detection and Genotype Calling from Massively Parallel Sequencing (MPS) DataGenetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European DescentIntroduction to deep sequencing and its application to drug addiction research with a focus on rare variants.Trps1 differentially modulates the bone mineral density between male and female mice and its polymorphism associates with BMD differently between women and men.Imputation of coding variants in African Americans: better performance using data from the exome sequencing projectApplying data envelopment analysis to preventive medicine: a novel method for constructing a personalized risk model of obesityRemoving reference mapping biases using limited or no genotype data identifies allelic differences in protein binding at disease-associated loci.Imputing Genotypes in Biallelic Populations from Low-Coverage Sequence Data.Powerful and Adaptive Testing for Multi-trait and Multi-SNP Associations with GWAS and Sequencing Data.Identity-by-descent estimation with population- and pedigree-based imputation in admixed family data.Inherited GATA3 variants are associated with Ph-like childhood acute lymphoblastic leukemia and risk of relapse.Identification of key contributors in complex population structures.FISH: fast and accurate diploid genotype imputation via segmental hidden Markov model.Association studies with imputed variants using expectation-maximization likelihood-ratio tests.Variation in the oxytocin receptor gene is associated with increased risk for anxiety, stress and depression in individuals with a history of exposure to early life stressGene-based sequencing identifies lipid-influencing variants with ethnicity-specific effects in African Americans.A meta-analysis of gene expression quantitative trait loci in brain.Challenges in conducting genome-wide association studies in highly admixed multi-ethnic populations: the Generation R Study.ALDsuite: Dense marker MALD using principal components of ancestral linkage disequilibriumA spatial haplotype copying model with applications to genotype imputation.Impact of genetic similarity on imputation accuracy.One Size Doesn't Fit All - RefEditor: Building Personalized Diploid Reference Genome to Improve Read Mapping and Genotype Calling in Next Generation Sequencing Studies.When Does Choice of Accuracy Measure Alter Imputation Accuracy Assessments?Family-based approaches: design, imputation, analysis, and beyond.Estimation of Genetic Relationships Between Individuals Across Cohorts and Platforms: Application to Childhood Height.Heritability and Genome-Wide Association Studies for Hair Color in a Dutch Twin Family Based Sample.Genome-wide association study identifies new susceptibility loci for adolescent idiopathic scoliosis in Chinese girlsGenetics of glucocorticoid-associated osteonecrosis in children with acute lymphoblastic leukemiaMicroRNAs Classify Different Disease Behavior Phenotypes of Crohn's Disease and May Have Prognostic Utility.Evaluation of Genome Wide Association Study Associated Type 2 Diabetes Susceptibility Loci in Sub Saharan Africans.Testing genetic association with rare variants in admixed populations.Genetic risk factors for the development of osteonecrosis in children under age 10 treated for acute lymphoblastic leukemia.A comprehensive SNP and indel imputability database.Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis.GenomeLaser: fast and accurate haplotyping from pedigree genotypes.Comparing performance of modern genotype imputation methods in different ethnicitiesAllelic heterogeneity in NCF2 associated with systemic lupus erythematosus (SLE) susceptibility across four ethnic populations.
P2860
Q27316407-35460643-82BE-48CE-A58D-06A92B01820AQ28393089-124B0BB0-5CDF-4429-8E65-2E2C859C902FQ28646494-91FFEBF4-BAE8-41F6-9EF3-A7E0D85FF4FDQ28659873-51312A23-B69A-44ED-8628-8522FFD6B78FQ30000080-CA8289B9-0CA1-41BA-BD82-528D5C06446BQ30408390-82F4A92D-C932-4F0A-BB83-25C9C1DBBB0AQ30415336-8E40456E-E4E6-42F5-9948-09550B7641E8Q30662194-E3FF4B02-9A9D-42BF-9742-91BD495E979BQ30951534-AE6F905C-3B0F-4F74-8D30-7F6126E190DBQ30982599-2AE7B08C-58EB-4531-8A0F-AA8DCD3D4FB8Q31034420-484C07BF-1500-44C8-861B-C9BC11409901Q31076621-21F62345-EC33-459C-BF53-6A6E9B4966B2Q31149273-0A6D9391-B4A8-4347-8AB2-FC2C823AAE7DQ33688248-BD3658DE-BD7B-42CB-BCC2-779E74D27AE4Q33693784-88A31FCB-5C5B-46E7-9096-953F27D43E0CQ33807685-7111587F-0EC8-43BD-B65F-46D7DE0EBB9DQ34482659-7158FBB6-A12A-4C4C-9C6F-484A937685D3Q34616947-89689282-5B85-4585-A0AA-D155B7B7FFF7Q35112657-A747A1E0-7938-4861-A405-61682A9FBC37Q35150211-3EFE0405-B407-4A59-AD24-4FE63CF6D578Q35266136-6D53CFAB-8C76-4C0B-8E76-36F9B9103363Q35534400-E383B3B1-C96F-446B-AC83-A7726B7E310EQ35586817-2B0AD143-6151-41F6-902D-EA94E1F3F6C7Q35700710-ECF841E9-2C13-4BA2-89FD-F11D2DC22F46Q35743902-6FF51415-C80B-4558-A48C-0EC4E84FE03DQ35803507-9AE5954E-94D5-451A-8DB2-E8A751A43ED3Q35920732-C8F031DE-6634-4754-A11E-E2BD00869185Q36031207-6BCC8DCF-D7F0-4E26-9F8F-DBDACA737B25Q36096473-1540AC83-0F38-443D-897A-E625755D7D95Q36128818-A418FB08-DDE1-4B47-A60E-5F09120B8EF6Q36143232-025EEE2B-41A6-4F98-8505-46F03B5730E1Q36155959-27829C56-A942-4081-BAFA-46F4532FACBCQ36309642-6DB1953A-50CB-47A9-BBFB-23C1EEF78A16Q36472658-3C8AEDA6-7DCA-43A7-A674-9691B9ACBF4EQ36547791-6ECB0E36-8E40-42C5-BCFA-90349D3C3E62Q36603849-43C9EDD0-9A9D-469F-9E82-BB4EEB68CAAEQ37193633-51ECC085-CA2A-41FF-AA07-CB08D7CD8FCFQ37237867-BAFCAC31-8BF8-43C7-87D9-445DE051514FQ37306979-ACE73C19-5DC0-4A5F-A1FE-E9E3EFFFD068Q37593029-4BCC79D3-9FD9-41B4-B414-A0F630E68E9B
P2860
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
@zh
2012年學術文章
@zh-hant
name
MaCH-admix: genotype imputation for admixed populations
@ast
MaCH-admix: genotype imputation for admixed populations
@en
type
label
MaCH-admix: genotype imputation for admixed populations
@ast
MaCH-admix: genotype imputation for admixed populations
@en
prefLabel
MaCH-admix: genotype imputation for admixed populations
@ast
MaCH-admix: genotype imputation for admixed populations
@en
P2093
P2860
P356
P1433
P1476
MaCH-admix: genotype imputation for admixed populations
@en
P2093
P2860
P356
10.1002/GEPI.21690
P577
2012-10-16T00:00:00Z