Genome-Wide Association Study (GWAS) on Special Human Phenotypes
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".
Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 278
Special Issue Editors
Interests: analysis of high-dimensional molecular genetic data; population genetics and integrative genome analyses including expression data and metabolomics; statistical/continuous modelling of diseases and physiological processes
Special Issues, Collections and Topics in MDPI journals
Interests: analysis of high-dimensional molecular genetic data; population genetics and integrative genome analyses including expression data and metabolomics; statistical/continuous modelling of diseases and physiological processes
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent years showed a dramatic increase in our insights into the pathomechanisms of human diseases and physiological processes, an increase driven by genome-wide association analysis. In particular, the analysis of ultra-large cohort studies and meta-analysis of multiple studies have dominated recent studies on human genetics of common diseases.
However, there are many traits and diseases where certain phenotypes are still not available in large numbers, making large-scale replication or meta-analysis an unachievable goal. This hampers the communication of important findings and the emergence of follow-up studies for rare phenotypes. However, novel statistical techniques integrating evidence from external data sources are available and can provide additional functional evidence for identified genetic associations.
In this Special Issue, we welcome reviews, new methods, and original articles covering genetic analyses on phenotypes related to traits or diseases that are not available in very large numbers. We consider a study size of >1000 as a minimum. To support the validity of identified genetic associations, a replication cohort is not considered mandatory, as we encourage the integration of supportive external data for validation purposes. Such secondary analyses include, but are not limited to, integration of expression, proteomics, or metabolomics data or genetic analysis of related phenotypes. We are looking forward to your contributions.
Prof. Dr. Markus Scholz
Dr. Holger Kirsten
Guest Editors
Manuscript Submission Information
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Keywords
- GWAS
- data integration
- integrative analysis
- external validation
- multi-omics
- human infrequent phenotypes
