What is GWASpi?

GWASpi in a nutshell:

  • A tool to perform Genome-Wide Association Studies
  • Written in Java, with Apache Derby, JFreeChart and NetCDF 3 technology
  • Executable locally in a GUI (Graphical User Interface) and via command line

Basic requirements to run GWASpi:

  • Standard PC or Mac
  • Linux, MacOS, Windows operating systems
  • Java 1.6 or higher
  • A minimum of 256 MB of RAM dedicated to the application, 1GB or higher recommended (1.5GB per 106 markers)
  • 5GB of Hard Disk space or more for GWAS data storage

. . . → Read More: What is GWASpi?

Scope of the Application

GWASpi is currently able to perform following operations within the class of Genome Wide Association Studies:

  1. Import of most common commercial and standard formats (see File Formats)
  2. Basic quality controls such as Sample and Marker missingness, heterozygosity as well as Hardy-Weinberg tests
  3. Allelic Association tests on Case/Control data
  4. Genotipic Association tests on Case/Control data
  5. Trend tests (Cochran-Armitage) on Case/Control data
  6. QQ-plots of above mentioned analysis
  7. Manhattan-plots of above mentioned analysis
  8. Reports and tables of above mentioned analysis and quality controls
  9. Integration of queries to several biological databases
  10. Data merging, extraction and export to PLINK, MACH, Beagle and Eigensoft’s SmartPCA input, as well as GWASpi format and tabulated CSV

Further formats, QC and analysis features are being considered for future releases. Please contact us at gwaspi at upf dot edu for requests. . . . → Read More: Scope of the Application

New features and bug-fixes in latest Release Candidate

New features and bug-fixes in latest Release Candidate GWASpi_RC_v2.0 Version as published in Bioinformatics Applications Notes

  • Added Strand Flipping feature
  • Bugfix in Matrix Translation feature

Read the list of changes . . . → Read More: New features and bug-fixes in latest Release Candidate

Introduction to GWASpi

Genome-wide Association Studies (GWAS) based on Single Nucleotide Polymorphism (SNP) arrays are the most widely used approach to detect loci associated to human traits. Due to the complexity of the methods and software packages available, each with its particular format requiring intricate management work-flows, the analysis of GWAS usually confronts scientists with steep learning curves.
Indeed, the wide variety of tools makes the parsing and manipulation of data the most time-consuming and error prone part of a study. To help solving these issues, we present GWASpi, a user-friendly, multi-platform, desktop-able application for the management and analysis of GWAS data, with a novel approach on database technologies to leverage the most out of commonly available desktop hardware. GWASpi is a start-to-finish GWAS management application, from raw data to results, containing the most common analysis tools. As a result, GWASpi is easy to use, both in Graphic User Interface as well as Command Line Interface, and reduces in up to two orders of magnitude the time needed to perform the fundamental steps of a GWAS. . . . → Read More: Introduction to GWASpi

GWASpi’s new webpage!

We decided to redesign our webpage and make it more user-friendly.

You will now be able to follow news through RSS feeds, and enjoy a more pleasent look-and feel as well as a more ergonomic site.