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LocusFocus: Web-based colocalization for the annotation and functional follow-up of GWAS

Author

Listed:
  • Naim Panjwani
  • Fan Wang
  • Scott Mastromatteo
  • Allen Bao
  • Cheng Wang
  • Gengming He
  • Jiafen Gong
  • Johanna M Rommens
  • Lei Sun
  • Lisa J Strug

Abstract

Genome-wide association studies (GWAS) have primarily identified trait-associated loci in the non-coding genome. Colocalization analyses of SNP associations from GWAS with expression quantitative trait loci (eQTL) evidence enable the generation of hypotheses about responsible mechanism, genes and tissues of origin to guide functional characterization. Here, we present a web-based colocalization browsing and testing tool named LocusFocus (https://locusfocus.research.sickkids.ca). LocusFocus formally tests colocalization using our established Simple Sum method to identify the most relevant genes and tissues for a particular GWAS locus in the presence of high linkage disequilibrium and/or allelic heterogeneity. We demonstrate the utility of LocusFocus, following up on a genome-wide significant locus from a GWAS of meconium ileus (an intestinal obstruction in cystic fibrosis). Using LocusFocus for colocalization analysis with eQTL data suggests variation in ATP12A gene expression in the pancreas rather than intestine is responsible for the GWAS locus. LocusFocus has no operating system dependencies and may be installed in a local web server. LocusFocus is available under the MIT license, with full documentation and source code accessible on GitHub at https://github.com/naim-panjwani/LocusFocus.

Suggested Citation

  • Naim Panjwani & Fan Wang & Scott Mastromatteo & Allen Bao & Cheng Wang & Gengming He & Jiafen Gong & Johanna M Rommens & Lei Sun & Lisa J Strug, 2020. "LocusFocus: Web-based colocalization for the annotation and functional follow-up of GWAS," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-8, October.
    • Handle: RePEc:plo:pcbi00:1008336
    DOI: 10.1371/journal.pcbi.1008336
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    References listed on IDEAS

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    1. Claudia Giambartolomei & Damjan Vukcevic & Eric E Schadt & Lude Franke & Aroon D Hingorani & Chris Wallace & Vincent Plagnol, 2014. "Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics," PLOS Genetics, Public Library of Science, vol. 10(5), pages 1-15, May.
    2. Xiaoquan Wen & Roger Pique-Regi & Francesca Luca, 2017. "Integrating molecular QTL data into genome-wide genetic association analysis: Probabilistic assessment of enrichment and colocalization," PLOS Genetics, Public Library of Science, vol. 13(3), pages 1-25, March.
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    2. Fasil Tekola-Ayele & Xuehuo Zeng & Suvo Chatterjee & Marion Ouidir & Corina Lesseur & Ke Hao & Jia Chen & Markos Tesfaye & Carmen J. Marsit & Tsegaselassie Workalemahu & Ronald Wapner, 2022. "Placental multi-omics integration identifies candidate functional genes for birthweight," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

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