Modern biological imaging produces vast amounts of data. At the CCI we have the infrastructure and expertise to be able to support users in the storage and analysis across the range of size scales from a few megabytes to terabytes.
Our staff include a Technical Specialist in Image Analysis to aid with your experimental design and post-acquisition quantitation. Please get in touch if you have any questions.
Reproducible research requires good quantitation. Users of the CCI have wide and varied projects which often require bespoke analysis solutions. Below are some examples of the type of analysis we do and teach on a regular basis. Please get in touch if you would like more information, or would like to arrange a meeting with our staff Image Analyst.
Whether you're interested in counting colonies on a plate, cells in a dish or zebrafish, enumeration of objects works in fundementally similar ways. Objects are segmented, then contiguous pixels are considered to be single objects.
Nuclei are just one example of objects that can be counted automatically.
These objects can then be analysed for area, shape, intensity or any number of other features. They can even be used as a mask with which to measure a different channel or timepoint.
Life exists in the temporal dimension. As such it's often scientifically interesting to follow objects over time. Maybe this is in order to track the changes in intensity or shape over time, but perhaps the movement itself is of interest to you?
All manner of imaging is amenable to tracking, including (as above) transmitted light.
At the CCI we can teach you how to track objects in two or three spatial dimensions over time and acrue dynamic data about your system. We have lots of experience working with tracking data so we can help you ask and answer the right questions.
When objects share spatial localisation, it is often suggestive of a meaningful interaction. There are many ways to biophysically assess interactions (for example using FRET) but sometimes a simple localisation can help to inform these descisions. Both pixel-based and object based colocalisation are useful tools depending upon the sample.
How much of your probe overlaps? What are the mean distances between neighbours?
Even the most trivial of manipulations such as contrast adjustments or cropping can be laborious when applied to hundreds or thousands of images. Many software packages can be automated via scripting or macros which can turn a 5-day job into a 5-minute job. If you find yourself repeatedly doing the same task over and over again, come and talk to us about automation. You (or your students!) will be glad you did!
As research scientists, we all need to communicate our findings, whether to the public, peers, funding bodies or PhD examination committees to name but a few. A good figure can help explain a highly complex subject or clarify a technique. Visualising your data can also help you to interpret your findings and spot problems or subtle events.
Some examples of visualising various types of data.
Fiji is a powerful, cross platform, extensible image processing program based on ImageJ. Plugins for common tasks such as registration, tracking and stitching come bundled, with lots of functionality available by adding more plugins. Through the Bio-Formats plugin, Fiji can pretty much open any proprietary microscopy formats that you throw at it. There is also great community support for Image Analysis and development questions.
Fiji is free to download and use.
Imaris is a high-end image data visualisation, segmentation and analysis software. It's particular strengths lie in segmentation of spots and volumes and the subsequent tracking of those objects over time.
The CCI has licences on two of its workstations. Access is free to users of the facilty and can be arranged (for a fee) for non-users.
MATLAB is "the language of technical computing", and has many proven applications for Image Analysis. We find it particularly useful for FRAP analysis and for handling large tracking datasets where matrix mathematics become invaluable. The online reference documentation and community are fantastic resources for those using MATLAB and there is a great getting started tutorial.
MATLAB is installed on all of our workstations, and is available to University of Liverpool Staff and Students via the MWS.
OMERO is an open source research data management software. Working on a server/client interface it allows for easy access and sorting of large amounts of Imaging data in their raw (ie. proprietary) formats. OMERO is developed by the openmicroscopy group at the University of Dundee but has many partners working to extend the platform. Data in OMERO can be interfaced with many platforms including ImageJ, KNIME, Icy & MATLAB.
OMERO is accessible via a web browser or via a downloadable client which is installed on all of the acquisition systems and workstations in the CCI.