SpotMap

SpotMap vs Other Software Solutions

SpotMap has been specifically developed to calculate HCP coverage using 2D gels and 2D Western blots, providing objective and reproducible results using a simple and fast workflow.

Other 2D gel analysis software exists, however these have typically been developed for analysis of differential expression.  SpotMap is also unique in comparison to using a contract research organisation (CRO) as no CRO currently uses SpotMap.

Here are comparisons between SpotMap and alternative approaches:

Comparison of SpotMap and PDQuest

  PDQuest SpotMap
Software development and support Current version released in 2005 – no development work since. Development started in 2014. Version 3 was released in May 2017. SpotMap has, and will contininue to be developed with feedback from existing customers.
Intended Purpose Developed for differential expression analysis, not HCP coverage calculation. Specifically developed for HCP coverage calculation between 2D gels and Western blots.
State-of-the-art Approach based on older spot-matching method. Approach based on next generation image alignment method.
Speed Time-consuming spot-matching and editing which often needs to be repeated. Rapid alignment, spot detection and use of filters for faster editing.See our coverage report where analysis of images was completed within 1 hour.
Ease-of-use Complex toolbox-based approach. Flexible yet simple workflow to support multiple experimental designs.

Direct comparison of SpotMap and PDQuest for determining HCP coverage.

A silver stained 2D gel was compared to a Western blot captured at 3 exposure times of 1.0, 3.2 and 5.5 seconds. Analysis was completed using PDQuest and SpotMap, the workflow of each software program and percentage coverage results were compared. Analysis using PDQuest took approximately 3.5 hours and provided percentage coverage results in a range of 11% across the three exposure times. SpotMap analysis took approximately 1 hour and provided percentage coverage results in a range of 1% across all exposure times.

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Comparison of SpotMap and DeCyder

  DeCyder SpotMap
Software development and support Discontinued late 2015. Development started in 2014. Version 3 was released in May 2017. SpotMap has been, and will continue to be,  developed with feedback from existing customers.
Intended Purpose Developed for differential expression analysis, not HCP coverage calculation. Specifically developed for HCP coverage calculation between 2D gel and Western blot.
State-of-the-art Approach based on older spot-matching method. Approach based on next generation image alignment method.
Flexibility DIGE only analysis. Single stain, DIGE and secondary staining comparisons in one package.
Speed Time-consuming spot-matching and editing which often needs to be repeated. Rapid alignment, spot detection and use of filters for faster editing.See our coverage report where analysis of images was completed within 1 hour.
Ease-of-use Complex toolbox-based approach. Flexible yet simple workflow to support multiple experimental designs.

Comparison of SpotMap and using a Contract Research Organisation (CRO)

 

  CRO SpotMap
Control and transparency The analysis is performed off site, often you receive a comprehensive report. This does not compare to understanding the data yourself. Perform the analysis in house, giving you control over the method and developing an understanding of the analysis . Giving you more confidence in the accuracy of the results.
Cost A CRO typically charges approximately $2000 to run a gel/blot and analyse HCP coverage. If you run 1 test per month, SpotMap costs the same as the annual cost of the CRO. It will pay for its self in the first year.
Speed Turnover times for results from a CRO can exceed 1 month. SpotMap analysis typically takes 1 hour to analyse 1 gel vs blot.
State-of-the-Art Technology CROs use technology developed for differential expression or even make spot comparisons by eye. SpotMap has been specifically developed for the analysis of anti-HCP antibody coverage. No CRO currently uses SpotMap.

 

See SpotMap in action:

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