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SameSpots Frequently asked questions

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General SameSpots Questions

What can I use to decide interesting spots?

There are many features to allow you to decide on interesting spots including:

  • Fold changes
  • P-values and Q-values
  • Correlation Analysis
  • Expression Profiles

How can I highlight interesting spots?

You can sort the spots on many criteria and use our “tagging” feature to group spots of interest together.

How can I pick interesting spots?

Using our picking method allows you to align a picking gel to the gels in the experiment. You can then produce picking lists for the spots you wish to mass spec.

Can I check my gel running quality?

Yes!
Our gel quality tool SpotCheck helps you objectively validate that your gel running meets your lab’s quality standards. It also highlights some common problems that occur during image capture.

View the SpotCheck application note here

Can I compare DIGE gels?

Yes!

DIGE experiments can be setup before alignment and the software automatically deals with all measurement calculations.

Can I account for gel distortions?

Yes!
Alignment makes it possible to accurately compare images by removing the positional variation introduced during the electrophoresis and imaging process.

How can I account for different gel loading?

This is accounted for by using normalisation. Normalisation is required in proteomics experiments to calibrate data between different sample runs. This corrects for systematic experimental variation when running samples (for example, differences in sample loading).

The effect of such systematic errors can be corrected by a unique gain factor for each sample – a scalar multiple that is applied to each feature abundance measurement.

How can I highlight interesting spots?

You can sort the spots on many criteria and use our “tagging” feature to group spots of interest together.

Can I calculate pI/MW?

Yes.

If one of the gels has a molecular weight marker on it and/or a pI strip or spots with known values then you can calculate the MW and pI for all spots.

Can I import interesting mass spectrometry data?

Yes.

Results from Mass Spec, including MASCOT searches, can be imported into the program so you can look at and review this information in the program.

Can I export results?

Yes.

All the calculations, spot numbers, images and output can be exported from the program. A HTML report can also be produced to show the results from the entire experiment.

Images

Can I check my image quality?

When adding images to the experiment they are checked for quality and any issues/notes are highlighted for you immediately before any further analysis is attempted. Poor image quality can make analysis of your gels difficult. It can increase subjectivity and make your results less accurate.

What checks does Image QC do and what can I do to improve my images?

Image QC looks at and checks that images:

  • Are greyscale
  • Have a high bit-depth
  • Have a high dynamic range
  • Are free from saturation
  • Have not been compressed or edited prior to analysis

For more information on image capture see the Image Capture Ebook

Can I edit my images?

Yes.

If your images require minor changes then you can edit them within the software without changing the original images. Edits include:

  • Flip images horizontally and vertically
  • Rotate images 90 degrees clockwise and anti-clockwise
  • Invert image
  • Crop image

Alignment

What is Alignment and what problem does it solve?

Alignment takes two images and overlays them in the same co-ordinate space so that a spot on image A will be in the same location as the matching spot on image B. Alignment makes it possible to accurately compare images by removing any positional variation introduced during the gel running and imaging processes.

What is the Reference Gel?

One gel is selected to be the reference gel at the start of the experiment. This gel is used as the base for alignment so all other gels are aligned to this one. One gel is selected automatically but you can change this if you wish. An image with lots of clear, representative spots is best. The Reference Gel is only used for alignment.

How does Alignment work?

One gel is selected to be the reference gel at the start of the experiment. This gel is used as the base for alignment so all other gels are aligned to this one. One gel is selected automatically but you can change this if you wish. An image with lots of clear, representative spots is best. The Reference Gel is only used for alignment.

Spot Detection, Filtering and Editing

What does Automatic Spot Detection do?

It takes a number of gel images and using advanced imaging techniques it creates a series of spot shapes which are used to create spot patterns (the spot map) that is used for all the images in the experiment. See the section on Spot Matching to understand the background to this method.

How can I check the spots created?

There are a number of modes available to check the results of the spot detection. Spots can be edited and/or filtered in the Filtering and Review Spots modes. Review Spots also allows you to review all the detected spots and look at their expression profiles.

Which images are used to calculate the spots?

By default all of the images in the experiment are used as a basis for the spot detection. However, before you detect the spots you can optionally deselect some images if you do not wish to use them to contribute.

What is Filtering and what happens to normalisation after Filtering?

The Filtering stage follows the automatic analysis of the aligned images that is performed after alignment (spot detection, matching, background subtraction and normalisation).

On completion of analysis the Filtering page will open displaying the spot detection. If required you can remove spots based on position, area, normalised volume and combinations of these spot properties.

Normalised Volumes are recalculated after any filtering is applied so any results noted in Review Spots (p-value, Fold, etc.) may change slightly.

How is the background level calculated?

In SameSpots, the background level for a spot is equal to the lowest intensity value of the image pixels outside the spot’s outline. The background level is then subtracted from the intensity value of every pixel inside the spot outline to determine the volume of the protein material in the spot.

How is the Spot Volume calculated?

The Volume is the integrated intensity of the spot with any calculated background subtracted. (This value is used in the calculation of Normalised volume).

The Raw spot volume is the sum of the Volume + Background.

How is the Fold difference calculated?

A fold difference is the ratio of normalised volumes of a single spot between gels. This can also be calculated on average normalised volumes of a single spot between groups of gels.

The Maximum fold difference refers to the fold difference in expression between 2 of the groups in the experiment. This is the fold difference of the groups with the highest and lowest average normalised volumes.

What do Expression profiles plot?

The normal expression profile view shows the log normalised spot profile (i.e. expression) values. Standardised profiles take these log normalised values and transforms them (centre and scale) to have mean = 0 and std deviation = 1. Basically, this allows you to compare the change in the profile for spots over a large dynamic range. An important point is that centering and scaling doesn’t change the correlation between the profiles.

Statistical Analysis

What is Principle Components Analysis (PCA)?

Principal components analysis calculates a linear projection of the data such that the first axis (Principal component 1) will show the largest variance that could be represented by the transform (i.e. a linear combination of translation, rotation, scaling). The second principal component is the best direction orthogonal to the first axis that accounts for the next largest chunk of the variance in the data. This is an ‘unsupervised’ technique (i.e. it does not use any knowledge of the grouping of the data) and as such is useful in finding if your data has the groupings you expect or if there are outliers in your data.

How do you use the PCA plot?

Principal components analysis (PCA) converts data into a form which allows us to visualize it in fewer dimensions. So in a PCA plot gels which have similar expression patterns will be close together whilst gels that have different expression patterns will be far apart. One use of PCA is to confirm that the gels group according to their expected experimental conditions. This can be used as a quality control to identify outlier gels. It is also possible to plot protein spot data in the PCA graph and this may allow us to identify spots which are contributing to observed differences between gel groups.

What is Correlation Analysis?

Correlation analysis is a technique which allows us to explore similarities between expression profiles of protein spots across multiple gels. Spots which vary in a similar way will have a high correlation value (with 1 indicating an exact match); spots which show opposing behaviour will have a large negative correlation value (with -1 indicating a perfect mismatch); spots which are not related will have a correlation value close to zero.

What are q-values, and why are they important?

Q-values are the name given to adjusted p-values. The method is used to account for the multiple testing problem and uses an optimised FDR approach to solve this problem.

Normalisation

Why normalise?

Normalisation is required in proteomics experiments to calibrate data between different sample runs. This corrects for systematic experimental variation when running samples (for example, differences in sample loading). The effect of such systematic errors can be corrected by a unique gain factor for each sample – a scalar multiple that is applied to each feature abundance measurement.

What calculations use the Normalised Volume?

All Fold changes use Normalised Volumes.

All statistics are based on the log of the Normalised Volume.

Why do we log the Normalised Volume?

Imagine you have two spots, one big and one small. These spots have been detected across several gels. Let’s assume that the spot data has been normalised. Now look at the range of values for the big spot and the small spot. You will see that the range for the small spot is less than the range for the big spot. In other words, the variance of the values for the small spot is less than the variance for the big spot. This is typical of proteomics data. As the mean expression level of spots gets higher, the variance of the spot data also increases. Now, most statistical tests require that the variance should be the same. So, we need to convert (transform) the data so that the new spot data has equal variance. This is called variance stabilisation. To stabilise the variance we use the log transform.

Experiment Design

What is Experiment Design Setup?

Many statistical tests compare 2 or more groupings of data (e.g. Control and Treated) to look at the differences between the groupings. Experiment Design is used to set up these groupings.

Can I compare different groupings in the same experiment?

Just create more than one “Experiment Design” and then when looking at the results on other pages you can choose which grouping to use. As soon as the experiment design is changed, all measurements and statistics are recalculated. The notes and tags will remain unchanged, so you can easily see how individual spots are behaving in different experiment design.

Spot Picking & Data Reporting

Can you create spot picking files?

Spot Picking occurs near the end of the process and allows you to set up the spot picking to pick off either one of the gels in the experiment or from an additional gel run for the purpose of picking off. In the case of DIGE the latter is the norm where a gel external to the experiment is used as the picking gel.

What is the Clip Gallery?

At every stage of the SameSpots workflow the images and data tables can be added to the Clip Gallery. The clip gallery makes it easier to capture images and tables from the software for the production of posters, publications and presentations. Images are saved as high resolution .png files (300 dpi). The saved images are retained as part of the experiment and are stored accordingly. This facility allows you to capture (high resolution) images that can be used in the development of specific reports and/or used as part of the process of publishing your experimental findings.

Can you export the Spot Measurements?

You can export to a CSV file (Comma Separated Values) that can be openedin Excel or other spreadsheet applications.

Is there an Experiment Report?

At the end of an experiment you can create an html report of the results. You can choose what to display including which spots to report on.There are 5 main sections to the report with multiple subsections:

  • Reference image
  • Experiment design
  • Spot table
  • Spot details
  • Experiment description

If you can’t find what you are looking for you can email our team

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