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README.md

README.md

Qtlizer: comprehensive QTL annotation of GWAS results

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                                                                                            + Introduction
                                                                                            + Installation
                                                                                            + Usage
                                                                                                     |-- Accepted query terms
                                                                                                     |-- Optional parameters
                                                                                                     |-- Meta information
                                                                                            + Try out online
                                                                                            + Authors
                                                                                            + Citation
                                                                                            + License

Introduction

This R package provides access to the Qtlizer web server. Qtlizer annotates lists of common small variants (mainly SNPs) and genes in humans with associated changes in gene expression using the most comprehensive database of published quantitative trait loci (QTLs).

Alternatively, the Qtlizer can be accessed by using a web-based GUI (http://genehopper.de/qtlizer). More information about usage and available datasets can be found at http://genehopper.de/help#qtlizer_docu.

Installation

devtools::install_github('matmu/Qtlizer')

Please note: A valid internet connection (HTTP port: 80) is required in order to install and use the package.

Usage

Simply call the function get_qtls() function to make requests to Qtilzer. The function utilizes a REST API (http://genehopper.de/rest) to query the annotation database. The QTL results will be returned as data frame or as GenomicRanges::GRanges object.

get_qtls('rs4284742 DEFA1')

Common seperators (space, comma, space + comma, ...) are accepted. It is also possible to pass your query with a vector:

get_qtls(c("rs4284742", "DEFA1"))

Accepted query terms

Accepted query terms are variant and gene identifiers of the form:

  • Rsid : rs + number e.g. "rs4284742"
  • reference:chr:pos e.g. "hg19:19:45412079" (Allowed references: hg19/GRCh37, hg38/GRCh38; accepted chromosomes are 1-22)
  • Gene symbol consisting of letters and numbers according to https://www.genenames.org/about/guidelines/

Optional parameters

  • corr: Correlation threshold based on linkage disequilibrium (LD) calculated from the 1000 Genomes Phase 3 European dataset. Optional value between 0 and 1. Default value is NA.

  • ld_method: Method to calculate correlation. Valid values are either "r2" (default) or "dprime".

     get_qtls("rs4284742", corr = 0.6, ld_method="r2")
  • return_obj: Determinse the format of the result. Value "dataframe" (default) returns a dara frame whereas "grange" returns a GenomicRanges::GRanges object.

  • ref_version: If output is a GRange object, the version of the reference genome is also considered. Accepted reference genome versions are "hg19" (default) or "hg38".

     get_qtls("rs4284742", return_obj = "grange", ref_version = "hg38")
  • max_terms: Number of queries made at a time. The default value is 5. It is recommended to not set the value higher than 5.

     get_qtls("rs4284742", max_terms = 4)

Meta information

Column descriptions of the received data frame can be accessed by calling:

df = get_qtls("rs4284742")
comment(df)

Try out online

If you want to try out the R package online, there is an example Google Colaboratory project at

https://colab.research.google.com/drive/1i1sjQHCjaw2wYzVBnXQ9iaghnk-jSU95#scrollTo=5Hi6sCe7SPFb

To run the project, make a private copy or open the project in playground mode and sign in to Google.

Authors

Matthias Munz
Julia Remes
University of Lübeck, Germany

Citation

Please cite the following article when using Qtlizer:

Munz M, Wohlers I, Simon E, Busch H, Schaefer A* and Erdmann J * (2018) Qtlizer: comprehensive QTL annotation of GWAS results. bioRxiv

License

GNU General Public License v3.0

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