Gene Expression

Automated image alignment for 2-D gel electrophoresis in a high-throughput proteomics pipeline

Andrew W. Dowsey¹, Michael J. Dunn² and Guang-Zhong Yang¹

¹Institute of Biomedical Engineering, Imperial College London, United Kingdom.

²Conway Institute of Biomolecular & Biomedical Research, University College Dublin, Ireland.

Submitted to Bioinformatics journal 21^st August 2007

Programs and Data

The RAIN 2-D gel alignment algorithm improves on the existing image registration approach of MIR with:

· A third order B-spline transformation that provides a realistic smooth deformation model of the 2-DE process.

· Volume-invariant warping through explicit modelling of expression density, which ensures protein abundance levels remain invariant under spot deformation.

· Relative bias-field correction of expression inhomogeneities between gels using a multi-resolution third order B-spline approach interleaved inside the image registration process.

· Shifted-log image model for variance stabilisation in the registration process.

· A registration strategy and validation for DIGE gels, for which previous image-based gel matching algorithms were unable to register reliably due to the increased bias and dynamic range.

· A GP-GPU (General Purpose Computation on Graphics Processing Units) implementation to harness the scientific parallel computing power available in modern graphics cards.

RAIN is implemented with GP-GPU techniques together with features found only on Nvidia graphics card hardware. Other vendors’ hardware (e.g. ATI, Matrox) will not work. The minimum requirement is an Nvidia Geforce 6 series graphics card with 128Mb of memory. More recent Nvidia graphics card should also be 100% compatible, but please note that the algorithm has only been tested on the following models: 6800Ultra, 6800Ultra Go, 7800GT, 7800GTX and 8800GTX. Further resources on GP-GPU can be found at:

· http://en.wikipedia.org/wiki/GPGPU: Introduction to GP-GPU techniques.

· http://ww.gpgpu.org: A comprehensive portal for GP-GPU research over the past five years.

· http://developer.nvidia.com/page/cg_main.html: Nvidia’s page on their Cg programming language for GPUs.

· J.D. Owens et al. (2007) A Survey of General-Purpose Computation on Graphics Hardware. Comp. Graph. Forum, 26, 2007, 80-113.

The command line program for Windows can be downloaded here. A Windows graphical interface to view gel images and perform MIR alignment can be downloaded here. The gel images used for validation can also be downloaded:

· Veeser et al. (4Mb)

· Imperial (48Mb)

· UCD Silver Stain (160Mb)

· UCD DIGE (260Mb)

If you have any problems or suggestions please email a.w.dowsey@imperial.ac.uk.