A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles

Most risk variants for brain disorders identified by genome-wide association studies reside in the noncoding genome, which makes deciphering biological mechanisms difficult. A commonly used tool, multimarker analysis of genomic annotation (MAGMA), addresses this issue by aggregating single nucleotid...

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Veröffentlicht in:	Nature neuroscience 2020-04, Vol.23 (4), p.583-593
Hauptverfasser:	Sey, Nancy Y. A., Hu, Benxia, Mah, Won, Fauni, Harper, McAfee, Jessica Caitlin, Rajarajan, Prashanth, Brennand, Kristen J., Akbarian, Schahram, Won, Hyejung
Format:	Artikel
Sprache:	eng
Schlagworte:	631/1647/48 631/208/191 631/208/205/2138 631/378/1689 Analysis Animal Genetics and Genomics Annotations Behavioral Sciences Biological Techniques Biomedical and Life Sciences Biomedicine Brain Brain - metabolism Brain diseases Brain Diseases - genetics Brain Diseases - metabolism Chromatin Chromatin - metabolism Computational neuroscience Gene expression Gene polymorphism Genes Genetic aspects Genetic markers Genetic Predisposition to Disease Genome-wide association studies Genomes Genomic analysis Genomics Gestation Humans Magma Mental disorders Neurobiology Neurodegenerative diseases Neurodevelopmental disorders Neurosciences Nucleotides Polymorphism Polymorphism, Single Nucleotide Risk Risk Factors Single-nucleotide polymorphism Software Target recognition technical-report Tissues
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