A master spot map identifying the location of all spots on the gel and
blot are created through spot detection. Spots on each image are
categorized as present or absent from this map. The present or absent
settings are used to identify spots common, missing or additional to the
images in a comparison and measure % coverage.
Why is a single spot map used for the analysis?
Using a single spot map allows you to directly compare matching
spots/features between images and easily identify spots absent from that
given image. Alignment places corresponding spots in the same coordinate
space on the images, this allows a single spot map to be used.
How is the single spot map generated?
User should detect spots on the gel first as stained gels are often more
defined then a western blot image. The spot outlines are then transferred
to the blot (this should be done after alignment as it helps to see where
the spots exist on the blot) then you can detect spots on the blot. This
will give you one single spot map.
Watch our video to see how SpotMap
creates a single spot map.
Why are some spot edits required?
Sometimes the automatic spot detection results need to be refined. Spot
outlines around the edge can be removed. Spot outlines in the middle can
be added, deleted, merged or split. Additional spots can be added to the
map. Our tests have shown that you can have different levels of editing
(little or a lot) and still get similar coverage results. It is key to be
consistent so that you get similar results across experiments.
Why are spot outlines larger than the spots in 2D mode?
In 2D mode spots may look like they extend beyond the spot boundaries but
in fact if you look at them in 3D mode they are in fact perfectly aligned
to the background. This video shows the difference in 2D and 3D mode in
real time and the ways you can quickly validate the software that you