Corporate Banner
Satellite Banner
Informatics
Scientific Community
 
Become a Member | Sign in
Home>News>This Article
  News
Return

Qlucore Announces Aid to Better Visualizations of Large Data Sets

Published: Tuesday, December 10, 2013
Last Updated: Tuesday, December 10, 2013
Bookmark and Share
New traffic-light Qlucore Projection Score indicates the usefulness of a Principal Component Analysis (PCA) representation.

Historically, scientists and researchers have been faced with a problem when looking at visualizations of large amounts of data, of whether the patterns they are seeing are statistically valid, or random.

Qlucore Projection Score is a unique functionality that will be available in the new version of Qlucore Omics Explorer 3.0. Projection Score will provide the user with information on how accurately the visual representation is actually portraying data.

The patent-pending Qlucore Projection Score technique is the brain child of Qlucore co-founder Magnus Fontes. It allows detailed comparison of representations obtained by PCA corresponding to different variable subsets, e.g., those obtained by variance filtering of a large data set.

The goal of exploratory visualization is to find a representation from which interpretable and potentially interesting information can be extracted, that is, one that contains structures and patterns that are likely to be non-random.

By following the evolution of the projection score in real time during variance filtering, the user can easily find the variable subset (and thus implicitly the variance cut-off) giving the most informative representation.

Magnus Fontes, the co-founder of Qlucore and developer of the Projection Score concept comments: "Qlucore is proud to be at the forefront of visualization technology for scientific research. The Projection Score technique is one which I have been working on for a considerable time and it will be very valuable in aiding research scientists to validate their data visualization work. The technique has been welcomed by my peers and I am delighted that it is now available on a commercial basis."

To compute the projection score for a given data set, the user must start by computing the fraction of the total variance that is captured by the first three principal components. Then, an estimate is taken for the expected value of the same entity for completely random data.

The projection score is defined as the difference between the square root of the observed quantity and the square root of the expected value for random data. Hence, a large value of the projection score means that the PCA representation of the observed representation contains much more information (variance) than the corresponding representation of a random data set of the same size, which suggests that there are non-random, potentially interesting structures present in the representation.

In contrast, a projection score close to zero indicates that the representation is not more informative than one of a random data set and that there are no broad, consistent patterns to be found by the PCA.

By monitoring the evolution of the projection score during variance filtering, the optimal variable subset can be found. In Qlucore Omics Explorer 3.0 the projection score is colored according to the displayed value. Red indicates a low projection score, yellow indicates a medium-high score and green corresponds to a high projection score.

In practice, almost all real data sets contain some non-random structure, and therefore it is very uncommon to get a projection score close to zero. The colours, and thus the boundaries between what is considered to be a "good" or a "bad" projection score, are based on our experience from applying the projection score to many different data sets, and should be interpreted mainly as rough guidelines suggesting the quality of the representations.

The projection score is a widely versatile technique that is applicable for a broad family of different statistical analyses. The statistical and technical details have been published by Magnus Fontes and Charlotte Soneson in the prestigous scientific journal BMC Bioinformatics in 2011.


Further Information

Join For Free

Access to this exclusive content is for Technology Networks Premium members only.

Join Technology Networks Premium for free access to:

  • Exclusive articles
  • Presentations from international conferences
  • Over 3,100+ scientific posters on ePosters
  • More than 4,500+ scientific videos on LabTube
  • 35 community eNewsletters


Sign In



Forgotten your details? Click Here
If you are not a member you can join here

*Please note: By logging into TechnologyNetworks.com you agree to accept the use of cookies. To find out more about the cookies we use and how to delete them, see our privacy policy.

Related Content

Qlucore, Nebion Collaborate
Partnership aims to address complementary use cases.
Friday, February 07, 2014
Using Qlucore Omics Explorer for Interpreting Leukemia Proteomics Data
Qlucore software has speeded up the process and enabled discovery for leukemia researcher Steven Kornblau.
Monday, November 18, 2013
New Research Aims to Stop ‘Blood Doping' During Cycling and Other Competitive Sports
As cyclists take to the roads of Surrey, England, the subject of blood doping raises its head once again.
Thursday, August 01, 2013
How it Works: Advanced Data Analysis Using Visualisation
Visualisation is a powerful tool for those working in molecular biology, here Qlucore offers a five-step method to ensure repeatable and significant results.
Monday, June 24, 2013
Qlucore Receives R&D Funding
VINNOVA Grant will speed the interactivity and visual feedback of Next Generation Sequencing (NGS) data analysis for scientists.
Monday, April 29, 2013
Researchers Develop Animal Free Methods for Testing Chemical Compounds for Allergens
EU-funded research project developing in vitro (‘out of body’) test strategies to reduce or replace animal testing use gene expression analysis software.
Monday, April 08, 2013
Qlucore Targets Academic and Commercial Biotech, Life Science Markets with Novo Newton Scientific Ltd
New alliance increases Qlucore's sales and marketing presence in Ireland, Spain, Italy and South Africa.
Thursday, January 24, 2013
NHS Urged to Prepare for ‘Genetic Revolution’
The ability to bring biologists into the data analysis phase will be key to achieving this important goal.
Monday, November 21, 2011
Qlucore to Expand its Marketing Efforts with New High-profile Appointment to its Board
New appointment coincides with the injection of new capital to increase market activities of its data analysis tool
Wednesday, November 25, 2009
Scientific News
Advancing Protein Visualization
Cryo-EM methods can determine structures of small proteins bound to potential drug candidates.
Gene Expression Controls Revealed
Researchers have modelled every atom in a key part of the process for switching on genes, revealing a whole new area for potential drug targets.
Making Genetic Data Easier to Search
Scripps team streamlines biomedical research by making genetic data easier to search.
Monovar Drills Down Into Cancer Genome
Rice, MD Anderson develop program to ID mutations in single cancer cells.
It’s Now Easier To Go With The Flow
Rice University tool simplifies comparison of flow cytometry data for laboratories.
Making Precision Medicine a Reality
Researchers are one step closer to understanding the genetic and biological basis of diseases like cancer, diabetes, Alzheimer’s and rheumatoid arthritis – and identifying new drug targets and therapies.
New Database for Sharing MS Clinical Trial Data
A new database containing nearly 2500 patient records from the placebo arms of nine multiple sclerosis (MS) clinical trials is now available for research by qualified investigators.
‘Precision Prevention’ for Colorectal Cancer
New risk prediction model — not yet ready for clinical use — incorporates genetic, lifestyle and environmental risk factors.
Characterizing Cancerous Genomic Variations
Tested on large tumor genomics database, REVEALER method allows researchers to connect genomics to cell function.
Uncovering Hidden Genomic Alterations that Drive Cancers
Tested on large tumor genomics database, REVEALER method allows researchers to connect genomics to cell function.
Scroll Up
Scroll Down
SELECTBIO

SELECTBIO Market Reports
Go to LabTube
Go to eposters
 
Access to the latest scientific news
Exclusive articles
Upload and share your posters on ePosters
Latest presentations and webinars
View a library of 1,800+ scientific and medical posters
3,100+ scientific and medical posters
A library of 2,500+ scientific videos on LabTube
4,500+ scientific videos
Close
Premium CrownJOIN TECHNOLOGY NETWORKS PREMIUM FOR FREE!