Introduction

Gene expression databases contain invaluable information about a range of cell states, but the question "Where is my gene of interest expressed?" remains one of the most difficult to systematically assess when relevant data is derived on different platforms. Barriers to integrating this data include disparities in data formats and scale, a lack of common identifiers, and the disproportionate contribution of a platform to the 'batch effect'. There are few purpose-built cross-platform normalization strategies, and most of these fit data to an idealized data structure, which in turn may compromise gene expression comparisons between different platforms. YuGene addresses this gap by providing a simple transform that assigns a modified cumulative proportion value to each measurement, without losing essential underlying information on data distributions or experimental correlates. The Yugene transform is applied to individual samples and is suitable to apply to data with different distributions. Yugene is robust to combining datasets of different sizes, does not require global renormalization as new data is added, and does not require a common identifier. YuGene was benchmarked against commonly used normalization approaches, performing favorably in comparison to quantile (RMA), Z-score or rank methods. Implementation in the www.stemformatics.org resource provides users with expression queries across stem cell related datasets. Probe performance statistics including poorly performing (never expressed) probes, and examples of probes/genes expressed in a sample-restricted manner are provided. The YuGene software is implemented as an R package available from CRAN.

Publications

  1. YuGene: a simple approach to scale gene expression data derived from different platforms for integrated analyses.
    Cite this
    Lê Cao KA, Rohart F, McHugh L, Korn O, Wells CA, 2014-04-01 - Genomics

Credits

  1. Kim-Anh Le Cao
    Developer

    Queensland Facility for Advanced Bioinformatics, The University of Queensland, Australia

  2. Florian Rohart
    Developer

    Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Australia

  3. Leo McHugh
    Developer

    Queensland Facility for Advanced Bioinformatics, The University of Queensland, Australia

  4. Othmar Korn
    Developer

    Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Australia

  5. Christine A Wells
    Investigator

    Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Australia

Community Ratings

UsabilityEfficiencyReliabilityRated By
0 user
Sign in to rate
Summary
AccessionBT001542
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionAustralia
Submitted ByChristine A Wells