Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

fastman: A fast algorithm for visualizing GWAS results using Manhattan and Q-Q plots

Soumya Subhra Paria, View ORCID ProfileSarthok Rasique Rahman, View ORCID ProfileKaustubh Adhikari
doi: https://doi.org/10.1101/2022.04.19.488738
Soumya Subhra Paria
aThe Open University, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sarthok Rasique Rahman
aThe Open University, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Sarthok Rasique Rahman
Kaustubh Adhikari
aThe Open University, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Kaustubh Adhikari
  • For correspondence: k.adhikari@ucl.ac.uk
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

Visualization of GWAS summary statistics, specifically P-values, as Manhattan plots is widespread in GWAS publications, and many popular software tools are available, such as the R package qqman. But there is substantial need for further development, such as the handling of non-human data. We provide a new R package, fastman, with major additional capabilities. It handles genomes of non-model organisms, even those at a draft stage, i.e. contigs that haven’t been compiled to chromosomes. Non-numeric chromosome IDs are supported. It supports plotting of other genetic scores, such as FST, D statistics, selection statistics such as PBS, or other kinds of GWAS statistics such as beta. Importantly, negative or two-tailed values are supported in this package. We implement a heuristic algorithm that drastically reduces plotting time for huge datasets without any loss of visual precision, while allowing for many different data types and missing data. We provide substantial additional flexibility in highlighting and annotation. In summary, we have developed a package fastman in R for fast and efficient visualization of GWAS results and other genomewide scores using Manhattan and Q-Q plots. The package can create plots directly from association outputs by PLINK. Alternatively, it can produce plots from any R data frame with custom columns and is equipped to handle big datasets with fast plot generation. It is available for public use on https://github.com/kaustubhad/fastman.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/kaustubhad/fastman

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted April 19, 2022.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
fastman: A fast algorithm for visualizing GWAS results using Manhattan and Q-Q plots
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
fastman: A fast algorithm for visualizing GWAS results using Manhattan and Q-Q plots
Soumya Subhra Paria, Sarthok Rasique Rahman, Kaustubh Adhikari
bioRxiv 2022.04.19.488738; doi: https://doi.org/10.1101/2022.04.19.488738
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
fastman: A fast algorithm for visualizing GWAS results using Manhattan and Q-Q plots
Soumya Subhra Paria, Sarthok Rasique Rahman, Kaustubh Adhikari
bioRxiv 2022.04.19.488738; doi: https://doi.org/10.1101/2022.04.19.488738

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4397)
  • Biochemistry (9624)
  • Bioengineering (7118)
  • Bioinformatics (24929)
  • Biophysics (12660)
  • Cancer Biology (9985)
  • Cell Biology (14395)
  • Clinical Trials (138)
  • Developmental Biology (7986)
  • Ecology (12141)
  • Epidemiology (2067)
  • Evolutionary Biology (16021)
  • Genetics (10947)
  • Genomics (14774)
  • Immunology (9899)
  • Microbiology (23732)
  • Molecular Biology (9502)
  • Neuroscience (51040)
  • Paleontology (370)
  • Pathology (1544)
  • Pharmacology and Toxicology (2690)
  • Physiology (4035)
  • Plant Biology (8687)
  • Scientific Communication and Education (1512)
  • Synthetic Biology (2404)
  • Systems Biology (6454)
  • Zoology (1349)