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A novel haplotype-based eQTL approach identifies genetic associations not detected through conventional SNP-based methods
Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2020.07.23.206391v1?rss=1
Authors: Al Bkhetan, Z., Chana, G., Soon Ong, C., Goudey, B., Kotagiri, R.
Abstract:
Motivation: The high accuracy of current haplotype phasing tools has enabled the interrogation of haplotype (or phase) information more widely in genetic investigations. Including such information in eQTL analysis complements SNP-based approaches as it has the potential to detect associations that may otherwise be missed. Results: We have developed a haplotype-based eQTL approach called eQTLHap to investigate associations between gene expression and haplotype blocks. Using simulations, we demonstrate that eQTLHap significantly outperforms typical SNP-based eQTL methods when the causal genetic architecture involves multiple SNPs. We show that phasing errors slightly impact the sensitivity of the proposed method (< 4%). Finally, the application of eQTLHap to real GEUVADIS and GTEx datasets finds 22 associations that replicated in larger studies or other tissues and could not be detected using a single-SNP approach. Availability: https://github.com/ziadbkh/eQTLHap
Copy rights belong to original authors. Visit the link for more info
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By Multimodal LLCLink to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2020.07.23.206391v1?rss=1
Authors: Al Bkhetan, Z., Chana, G., Soon Ong, C., Goudey, B., Kotagiri, R.
Abstract:
Motivation: The high accuracy of current haplotype phasing tools has enabled the interrogation of haplotype (or phase) information more widely in genetic investigations. Including such information in eQTL analysis complements SNP-based approaches as it has the potential to detect associations that may otherwise be missed. Results: We have developed a haplotype-based eQTL approach called eQTLHap to investigate associations between gene expression and haplotype blocks. Using simulations, we demonstrate that eQTLHap significantly outperforms typical SNP-based eQTL methods when the causal genetic architecture involves multiple SNPs. We show that phasing errors slightly impact the sensitivity of the proposed method (< 4%). Finally, the application of eQTLHap to real GEUVADIS and GTEx datasets finds 22 associations that replicated in larger studies or other tissues and could not be detected using a single-SNP approach. Availability: https://github.com/ziadbkh/eQTLHap
Copy rights belong to original authors. Visit the link for more info