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Schilder BM, Humphrey J, Raj T. echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline. Bioinformatics. 2021;doi: 10.1093/bioinformatics/btab658.
Schilder, B. M., Humphrey, J., & Raj, T. (2021). echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline. Bioinformatics (Oxford, England), . https://doi.org/10.1093/bioinformatics/btab658
Schilder, Brian M, et al. "echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline." Bioinformatics (Oxford, England) vol. (2021). doi: https://doi.org/10.1093/bioinformatics/btab658
Schilder BM, Humphrey J, Raj T. echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline. Bioinformatics. 2021 Sep 16; doi: 10.1093/bioinformatics/btab658. Epub 2021 Sep 16. PMID: 34529038.
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Bioinformatics. 2021 Sep 16; doi: 10.1093/bioinformatics/btab658. Epub 2021 Sep 16.

echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline.

Bioinformatics (Oxford, England)

Brian M Schilder, Jack Humphrey, Towfique Raj

Affiliations

  1. Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
  2. Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
  3. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
  4. Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
  5. Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.

PMID: 34529038 DOI: 10.1093/bioinformatics/btab658

Abstract

SUMMARY: echolocatoR integrates a diverse suite of statistical and functional fine-mapping tools in order to identify, test enrichment in, and visualize high-confidence causal consensus variants in any phenotype. It requires minimal input from users (a summary statistics file), can be run in a single R function, and provides extensive access to relevant datasets (e.g. reference linkage disequilibrium panels, quantitative trait loci, genome-wide annotations, cell-type-specific epigenomics), thereby enabling rapid, robust and scalable end-to-end fine-mapping investigations.

AVAILABILITY AND IMPLEMENTATION: echolocatoR is an open-source R package available through GitHub under the MIT license: https://github.com/RajLabMSSM/echolocatoR.

SUPPLEMENTARY INFORMATION: Installation instructions (with an optional conda environment to minimize dependency conflicts), vignettes, example data, documentation of all functions and annotation datasets, as well as source code can be found in the echolocatoR website:https://rajlabmssm.github.io/echolocatoR In addition, we have created the echolocatoR Fine-mapping Portal which allows anyone to interactively visualize and download echolocatoR fine-mapping results across multiple traits: https://rajlab.shinyapps.io/Fine_Mapping_Shiny.

© The Author(s) (2021). Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected].

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