| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/bioinformatics/HormozdiariKYPE15 |
| P356 | DOI | 10.1093/BIOINFORMATICS/BTV240 |
| P932 | PMC publication ID | 4542778 |
| P698 | PubMed publication ID | 26072484 |
| P5875 | ResearchGate publication ID | 278331929 |
| P50 | author | Bogdan Pasaniuc | Q56555817 |
| Eleazar Eskin | Q62673408 | ||
| P2093 | author name string | Farhad Hormozdiari | |
| Wen-Yun Yang | |||
| Gleb Kichaev | |||
| P2860 | cites work | Genome-wide association analyses identify 18 new loci associated with serum urate concentrations | Q24620065 |
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| Linkage disequilibrium in humans: models and data | Q30654298 | ||
| Integrating functional data to prioritize causal variants in statistical fine-mapping studies | Q30865659 | ||
| Rapid and accurate multiple testing correction and power estimation for millions of correlated markers | Q33432685 | ||
| Leveraging genetic variability across populations for the identification of causal variants. | Q33571814 | ||
| Fast and accurate imputation of summary statistics enhances evidence of functional enrichment | Q34285337 | ||
| Identifying causal variants at loci with multiple signals of association | Q34336624 | ||
| A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene | Q34651283 | ||
| Increasing power of groupwise association test with likelihood ratio test | Q35550128 | ||
| Genome-wide association mapping of quantitative traits in outbred mice | Q35771644 | ||
| Incorporating prior information into association studies | Q36022170 | ||
| Efficient control of population structure in model organism association mapping | Q36515832 | ||
| Increasing power in association studies by using linkage disequilibrium structure and molecular function as prior information | Q36517959 | ||
| Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits | Q36670925 | ||
| Improved linear mixed models for genome-wide association studies | Q36683291 | ||
| Genome-wide association studies in mice | Q36763587 | ||
| Elucidating the role of gonadal hormones in sexually dimorphic gene coexpression networks | Q37125958 | ||
| Bayesian refinement of association signals for 14 loci in 3 common diseases | Q37217525 | ||
| Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis | Q37322100 | ||
| Genome-wide efficient mixed-model analysis for association studies | Q41961596 | ||
| DIST: direct imputation of summary statistics for unmeasured SNPs | Q42931079 | ||
| FaST linear mixed models for genome-wide association studies | Q46661213 | ||
| P275 | copyright license | Creative Commons Attribution-NonCommercial 4.0 International | Q34179348 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P433 | issue | 12 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | complex trait | Q55608248 |
| P304 | page(s) | i206-13 | |
| P577 | publication date | 2015-06-01 | |
| P1433 | published in | Bioinformatics | Q4914910 |
| P1476 | title | Identification of causal genes for complex traits | |
| P478 | volume | 31 |
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| Q64240282 | Genetics and epigenetics of autism spectrum disorder-current evidence in the field |
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| Q37336953 | Joint Bayesian inference of risk variants and tissue-specific epigenomic enrichments across multiple complex human diseases |
| Q57030056 | Large-scale transcriptome-wide association study identifies new prostate cancer risk regions |
| Q91959027 | Leveraging allelic imbalance to refine fine-mapping for eQTL studies |
| Q36758653 | Multiple testing correction in linear mixed models |
| Q28550282 | Network Analysis of Genome-Wide Selective Constraint Reveals a Gene Network Active in Early Fetal Brain Intolerant of Mutation |
| Q52372478 | New considerations for hiPSC-based models of neuropsychiatric disorders. |
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| Q52566012 | Prostate Cancer Genomics: Recent Advances and the Prevailing Underrepresentation from Racial and Ethnic Minorities. |
| Q30827855 | Pure and Confounded Effects of Causal SNPs on Longevity: Insights for Proper Interpretation of Research Findings in GWAS of Populations with Different Genetic Structures |
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