Synopsis of Social media discussions
Several discussions praise FUMA's integration of biological data and visualization tools, describing it as a 'game changer' for post-GWAS analysis; the tone underscores enthusiasm about its potential to improve research efficiency and discovery, particularly by reducing time-consuming tasks and facilitating clearer interpretation of complex data.
Agreement
Moderate agreementMost discussions acknowledge the usefulness of FUMA in streamlining post-GWAS annotation and data visualization, indicating general support.
Interest
High level of interestPosts show high interest by highlighting how FUMA can address key challenges in identifying causal variants and improve research workflows.
Engagement
Moderate level of engagementSome discussions delve into specific features like gene prioritization and visual tools, reflecting active engagement.
Impact
Moderate level of impactComments suggest that FUMA could significantly accelerate genetic research, implying a moderate to high impact on the field.
Social Mentions
YouTube
4 Videos
1 Posts
News
4 Articles
Metrics
Video Views
162
Total Likes
4
Extended Reach
1,758
Social Features
9
Timeline: Posts about article
Top Social Media Posts
Posts referencing the article
Genetic Association Mapping and Annotation with FUMA Explained
Genomewide association studies face challenges in identifying causal variants, especially in noncoding regions. FUMA streamlines GWAS annotation, gene prioritization, and data visualization to facilitate hypothesis generation about genetic variants.
Genetic Association Mapping and Annotation Using FUMA Tool
This video discusses the challenges of identifying causal variants in GWAS and introduces FUMA, a web-based platform that integrates biological data to annotate results, prioritize genes, and visualize data for efficient hypothesis generation.
Efficient Genetic Association Mapping and Annotation with FUMA
This video discusses FUMA, a web-based platform for annotating GWAS results, prioritizing genes, and visualizing data to identify causal variants, addressing challenges in genome-wide association studies.
Genetic Associations Analysis with FUMA for GWAS Data Interpretation
This video introduces FUMA, a web-based platform designed to annotate GWAS results, prioritize genes, and visualize data, addressing the challenge of identifying causal variants in genetic association studies.
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Functional mapping and annotation of genetic associations with FUMA https://t.co/6Zp9oYtGF3
view full postMarch 6, 2022
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Abstract Synopsis
- The main challenge in genomewide association studies (GWAS) is identifying causal variants since most significant hits are in noncoding regions and linkage disequilibrium spreads effects across multiple variants.
- Post-GWAS annotation is essential for selecting the most likely causal variants, but existing resources are often time-consuming and lack integrated visual tools.
- FUMA is a web-based platform that integrates various biological data to help annotate GWAS results, prioritize genes, and visualize data, thus streamlining the process of generating testable hypotheses about causal genetic variants.]
Diego Forero MD, PhD
@daforerog (Twitter)