Dr. Andrey Shabalin’s Select Publications
2019
Anderson, J.S., Shade, J., DiBlasi, E., Shabalin, A.A. & Docherty, A.R. Polygenic risk scoring and prediction of mental health outcomes. Curr Opin Psychol 27, 77-81 (2019). doi:10.1016/j.copsyc.2018.09.002
Chan, R.F. et al. Independent Methylome-Wide Association Studies of Schizophrenia Detect Consistent Case-Control Differences. Schizophr Bull (2019). doi:10.1093/schbul/sbz056
Clark, S.L. et al. A methylation study of long-term depression risk. Mol Psychiatry (2019). doi:10.1038/s41380-019-0516-z
2018
Aberg, K.A., Chan, R.F., Xie, L., Shabalin, A.A. & van den Oord, E. Methyl-CpG-Binding Domain Sequencing: MBD-seq. Methods Mol Biol 1708, 171-189 (2018). doi:10.1007/978-1-4939-7481-8_10
Aberg, K.A. et al. Methylome-wide association findings for major depressive disorder overlap in blood and brain and replicate in independent brain samples. Mol Psychiatry (2018). doi:10.1038/s41380-018-0247-6
Aberg, K.A. et al. Convergence of evidence from a methylome-wide CpG-SNP association study and GWAS of major depressive disorder. Transl Psychiatry 8, 162 (2018). doi:10.1038/s41398-018-0205-8
Clark, S.L. et al. A Whole Methylome Study of Ethanol Exposure in Brain and Blood: An Exploration of the Utility of Peripheral Blood as Proxy Tissue for Brain in Alcohol Methylation Studies. Alcohol Clin Exp Res 42, 2360-2368 (2018). doi:10.1111/acer.13905
Coon, H. et al. Genome-wide significant regions in 43 Utah high-risk families implicate multiple genes involved in risk for completed suicide. Mol Psychiatry (2018). doi:10.1038/s41380-018-0282-3
Docherty, A.R. et al. Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative. Schizophr Bull 44, S460-s467 (2018). doi:10.1093/schbul/sby059
Han, L.K.M. et al. Epigenetic Aging in Major Depressive Disorder. Am J Psychiatry 175, 774-782 (2018). doi:10.1176/appi.ajp.2018.17060595
Li, G., Shabalin, A.A., Rusyn, I., Wright, F.A. & Nobel, A.B. An empirical Bayes approach for multiple tissue eQTL analysis. Biostatistics 19, 391-406 (2018). doi:10.1093/biostatistics/kxx048
Palowitch, J., Shabalin, A., Zhou, Y.H., Nobel, A.B. & Wright, F.A. Estimation of cis-eQTL effect sizes using a log of linear model. Biometrics 74, 616-625 (2018). doi:10.1111/biom.12810
Shabalin, A.A. et al. RaMWAS: fast methylome-wide association study pipeline for enrichment platforms. Bioinformatics 34, 2283-2285 (2018). doi:10.1093/bioinformatics/bty069
Xia, H. et al. Building a schizophrenia genetic network: transcription factor 4 regulates genes involved in neuronal development and schizophrenia risk. Hum Mol Genet 27, 3246-3256 (2018). doi:10.1093/hmg/ddy222
2017
Aberg, K.A. et al. A MBD-seq protocol for large-scale methylome-wide studies with (very) low amounts of DNA. Epigenetics 12, 743-750 (2017). doi:10.1080/15592294.2017.1335849
Battle, A. et al. Genetic effects on gene expression across human tissues. Nature 550, 204-213 (2017). doi:10.1038/nature24277
Chan, R.F. et al. Enrichment methods provide a feasible approach to comprehensive and adequately powered investigations of the brain methylome. Nucleic Acids Res 45, e97 (2017). doi:10.1093/nar/gkx143
Clark, S.L. et al. Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence. Alcohol Clin Exp Res 41, 711-718 (2017). doi:10.1111/acer.13352
Hattab, M.W. et al. Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable approaches in empirical studies. Genome Biol 18, 24 (2017). doi:10.1186/s13059-017-1148-8
Li, X. et al. The impact of rare variation on gene expression across tissues. Nature 550, 239-243 (2017). doi:10.1038/nature24267
Saha, A. et al. Co-expression networks reveal the tissue-specific regulation of transcription and splicing. Genome Res 27, 1843-1858 (2017). doi:10.1101/gr.216721.116
Tan, M.H. et al. Dynamic landscape and regulation of RNA editing in mammals. Nature 550, 249-254 (2017). doi:10.1038/nature24041
Tukiainen, T. et al. Landscape of X chromosome inactivation across human tissues. Nature 550, 244-248 (2017). doi:10.1038/nature24265
Yang, F., Wang, J., Pierce, B.L. & Chen, L.S. Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis. Genome Res 27, 1859-1871 (2017). doi:10.1101/gr.216754.116