Rxivist logo

DISSECT: A new tool for analyzing extremely large genomic datasets

By Oriol Canela-Xandri, Andy Law, Alan Gray, John A. Woolliams, Albert Tenesa

Posted 05 Jun 2015
bioRxiv DOI: 10.1101/020453 (published DOI: 10.1038/ncomms10162)

Computational tools are quickly becoming the main bottleneck to analyze large-scale genomic and genetic data. This big-data problem, affecting a wide range of fields, is becoming more acute with the fast increase of data available. To address it, we developed DISSECT, a new, easy to use, and freely available software able to exploit the parallel computer architectures of supercomputers to perform a wide range of genomic and epidemiologic analyses which currently can only be carried out on reduced sample sizes or in restricted conditions. We showcased our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using Mixed Linear Model analysis. We analyzed simulated traits from half a million individuals genotyped for 590,004 SNPs using the combined computational power of 8,400 processor cores. We found that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large numbers of training individuals.

Download data

  • Downloaded 1,459 times
  • Download rankings, all-time:
    • Site-wide: 7,145 out of 101,301
    • In bioinformatics: 1,212 out of 9,292
  • Year to date:
    • Site-wide: 83,595 out of 101,301
  • Since beginning of last month:
    • Site-wide: 84,885 out of 101,301

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News

  • 20 Oct 2020: Support for sorting preprints using Twitter activity has been removed, at least temporarily, until a new source of social media activity data becomes available.
  • 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
  • 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
  • 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
  • 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
  • 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
  • 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
  • 22 Jan 2019: Nature just published an article about Rxivist and our data.
  • 13 Jan 2019: The Rxivist preprint is live!