SpotMap has a simple 5 step workflow that produces objective and reliable results from analysis of 2D gels and Western blots in as little as 1 hour!
This simple workflow allows easy analysis of images in any combination of 2D gels and Western blots. Follow the links below to see the workflow of SpotMap in action:
5 step workflow of SpotMap
1. Images – 2. Align – 3. Spots – 4. Match Spots – 5. Results
Images are automatically quality checked when uploaded to the software, giving you instant feedback and confidence in your results. Images QC looks at:
- Colour depth
- Image compression
- Dynamic range
- Image stretching
- Intensity levels
A base image is selected which is used as the alignment target, the basis for the automatic spot detection and the default image for comparison in results. Tools are available within the software to edit the images.
Images with quality issues are highlighted by a red outline. Images with striped red outlines require inverting prior to starting the analysis.
Alignment is a unique method that addresses the challenge of comparing different spot patterns commonly seen between 2D gels and Western blots. It allows corresponding spots on each image to be located in the same coordinate space.
Alignment is performed at the pixel level to provide direct and accurate comparison of images. Alignment is completed automatically or manually. Manual vectors are added to assist alignment of images where large positional differences exist.
The image to be aligned (green) is overlaid on the base image (purple) and vectors are added to align the images. The alignment is checked using the different viewing panes.
A master spot map is created which identifies the location of all spots on all images in the analysis. Automatic spot detection followed by refinement creates the initial spot map of the base image. This initial spot map is then overlaid on each other image in the analysis and any additional spots are added to create the master spot map.
3A. Creating the initial spot map
Automatic spot detection creates an initial spot map of 1000’s of spots quickly and objectively. Spot detection sensitivity can be optimised by the user using the following parameters:
- Peak sensitivity
- Remove background
- Set an area of interest
The automatic spot detection is then refined to remove any non-spot features using the tools available:
- Select spots to use as selection criteria to run objective filters.
- Freehand edit spots.
- Add spots missed by the auto detection.
- Split 2 spots automatically detected as 1.
- Merge fragmented spots.
- Delete non-spot features.
3B. Checking the spot map
The initial spot map is overlaid on each image in turn and checked to ensure it identifies all spots on every image. Any additional spots are added to the map using the tools available:
- Freehand draw spots onto the map.
- Add spots missed from the map.
- Split spots where one is present on previous images but two are present on the current.
Automatic spot detection followed by refinement creates the initial spot map.
The initial spot map is overlaid on each image, any additional spots are added to create the master spot map.
3. Match Spots
The master spot map is overlaid on each image in turn and spot presence or absence is categorised. Spot presence is used to calculate percentage coverage and identify spots unique to each image.
Spots are categorised as present or absent by using filters to objectively determine presence based on spot measurements or by manual selection.
Each spot sin the spot map is categorised as present or absent on each image. Present spots are indicated by blue outlines, absent spots are pink.
The results page presents top line results of each image compared to the base image; percentage coverage, spot numbers and heat maps of spot presence are presented. Results can be further investigated in 1 vs 1 comparisons of images or comparisons of sub-sets of spots or areas of the spot map.
All data can be easily exported from the analysis directly into reports and presentations by simple drag and drop from the Data Access window.
Coverage % = N Secondary image Spots / N Total Spots present on Base image and Secondary image x 100.
Results of the whole analysis, 1 vs 1 image comparisons and spot selections are presented. All data from the analysis can be exported using the Data Access window.