I performed an analysis for a specific gene/region of interest using GWAS summary statistics for a binary phenotype (+/- disease). Using the corrected p values in the summary statistics and mapping in FUMA, I found a significant missense/coding SNP, with p=0.025. Other papers have shown this SNP leads to a less functional protein. This SNP was not in LD with the other sig SNPs (intronic/non-coding). Could it be an independent SNP? Beta is 0.002 and MAF is 0.005. Is it possible this SNP is a false positive due to its rarity? Population size is n=400k and cases n=1100. Any help would be appreciated!
Dear Cate, I am sorry to say that the possibility of a false positive is ever present when dealing with massive testing, this is why the great part of correlative studies on single variables basis are increasingly discarded, see for example
https://academic.oup.com/jrssig/article/8/3/116/7030037
https://www.sciencedirect.com/science/article/abs/pii/S0895435605000235
Article Why Most Published Research Findings Are False
This is why I suggest you to shift toward more 'integrativeì kind of research trying and detect groups of correlated mutations instead of single SNPs
Article Pathway-Based Analysis for Genome-Wide Association Studies U...
Best
Alessandro
What is rational is actual and what is actual is rational. Despite the possibility of false positives, the biological function of the SNP cannot be completely denied. It may be possible to expand the sample size for cross-lineage meta-analysis. Of course, it can also be interpreted in the light of the current results, perhaps this snp is really interesting, despite its MAF=0.005
Analysis of the information you provided:
1. Significance: The corrected p-value of 0.025 suggests that the missense/coding SNP is statistically significant. However, it's important to consider the multiple testing correction applied, as it can affect the threshold for significance.
2. Functional impact: The fact that other papers have shown this SNP to lead to a less functional protein adds further support to its potential role in the phenotype of interest. It suggests that the SNP might have a functional impact on the gene's protein product.
3. LD with other significant SNPs: As you mentioned, the missense/coding SNP is not in linkage disequilibrium (LD) with the other significant SNPs in the region. This suggests that it represents an independent genetic variant influencing the phenotype, rather than being in LD with another causal variant.
4. Rarity and false positive: The SNP's low minor allele frequency (MAF) of 0.005 indicates that it is quite rare in the population. Rare variants can pose challenges in terms of statistical power and increased probability of false positives. Given the population size of 400k and the number of cases (n=1100), it is possible that the rarity of the SNP could contribute to increased uncertainty in the association results.
To further validate the association and assess the potential false positive rate, it would be beneficial to consider additional evidence, such as functional studies or replication in independent cohorts. Additionally, performing appropriate statistical analyses, such as replication analysis, permutation testing, or assessing genomic control inflation factors, can help evaluate the robustness of the association and minimize potential false positives.
It is advisable to consult with experts in the field or bioinformatics/statistical geneticists who can provide more specialized guidance based on your specific dataset and research question.
Hope it helps:credit AI
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