Fall desk cleaning

2010-12-27

Here are a few papers dealing with genetic epidemiology that I should have read for a while.

  1. Johnson et al., Accounting for multiple comparisons in a genome- wide association study, BMC Genomics 2010, 11:724
  2. Wang, Direct assessment of multiple testing correction in case-control association studies with related individuals, Genetic Epidemiology 2010 35(1):70
  3. Manning et al., Meta-analysis of gene-environment interaction: joint estimation of SNP and SNP × environment regression coefficients, Genetic Epidemiology 2010 35(1):11
  4. Han et al., Postassociation cleaning using linkage disequilibrium information, Genetic Epidemiology 2010 35(1):1
  5. Schwender et al., Testing SNPs and sets of SNPs for importance in association studies, Biostatistics 2010 12(1):18
  6. Kutalik et al., Methods for testing association between uncertain genotypes and quantitative traits, Biostatistics 2010 12(1):1
  7. Mueller et al., QuACN: an R package for analyzing complex biological networks quantitatively, Bioinformatics 2010 27(1):140
  8. García-Alcalde et al., Paintomics: a web based tool for the joint visualization of transcriptomics and metabolomics data, Bioinformatics 2010 27(1):137
  9. Abo et al., Automated construction and testing of multi-locus gene-gene associations, Bioinformatics 2010 27(1):134
  10. Jia et al., dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks, Bioinformatics 2010 27(1):95
  11. He and Lin, A variable selection method for genome-wide association studies, Bioinformatics 2010 27(1):1
  12. de Moor et al., Meta-analysis of genome-wide association studies for personality, Molecular Psychiatry 2010
  13. Caceres et al., Multiple correspondence discriminant analysis: An application to detect stratification in copy number variation, Statistics in Medicine 2010 29(30):3284
  14. Bremer et al., Copy number variation characteristics in subpopulations of patients with autism spectrum disorders, American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 2010
  15. Kistner-Griffin et al., Parent-of-origin effects of the serotonin transporter gene associated with autism, American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 2010
  16. Lee et al., Control of Population Stratification by Correlation-Selected Principal Components, Biometrics 2010
  17. Karwautz et al., Gene–environment interaction in anorexia nervosa: relevance of non-shared environment and the serotonin transporter gene, Molecular Psychiatry 2010
  18. So and Sham, A Unifying Framework for Evaluating the Predictive Power of Genetic Variants Based on the Level of Heritability Explained, PLoS Genetics 2010
  19. Leoutsakos et al., Incorporating scientific knowledge into phenotype development: Penalized latent class regression, Statistics in Medicine 2010
  20. Milne et al., Flapjack—graphical genotype visualization, Bioinformatics 2010 26(24):3133
  21. Hoehndorf et al., Interoperability between phenotype and anatomy ontologies, Bioinformatics 2010 26(24):3112
  22. Yang and Bickel, Minimum Description Length and Empirical Bayes Methods of Identifying SNPs Associated with Disease, Collection of Biostatistics Research Archive 2010
  23. Ilott et al., Genetic influences on attention deficit hyperactivity disorder symptoms from age 2 to 3: A quantitative and molecular genetic investigation, BMC Psychiatry 2010 10:102
  24. Furney et al., Genome-wide association with MRI atrophy measures as a quantitative trait locus for Alzheimer’s disease, Molecular Psychiatry 2010
  25. Dineen et al., Ensemble approach combining multiple methods improves human transcription start site prediction, BMC Genomics 2010, 11:677
  26. Rijsdijk et al., Heritability estimates for psychotic symptom dimensions in twins with psychotic disorders, American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 2010 156(1):89
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Articles with the same tag(s):

Data Science from Scratch
Stata for health researchers
R Graphs Cookbook
Bad Data
Data science at the command-line
Reproducible research with R
Twenty canonical questions in machine learning
Do a large amount of consulting
Dose finding studies and cross-over trials
Evidence-based medicine and clinical diagnosis

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