By using a tool known as a ‘heat map’ alongside dynamic PCA analysis, scientists have yet another way of visualising their data, since heat maps can take the values of a variable in a two-dimensional map and represent them as different colours. Because modern heat maps use sophisticated mapping techniques to represent this data (as opposed to standard charting and graphing techniques), they can provide a view of data that is simply not possible to achieve with simple charts and graphs.
Also, because they are often obtained from DNA microarrays, biology heat maps are often used to represent the level of expression of many genes across a number of comparable samples, such as cells in different states or samples from different patients. Heat maps are also popular for their ability to be dynamically updated when any filter parameters are changed.
A group of scientists studying the human eye at the Division of Ophthalmology and Visual Sciences at Queen’s Medical Centre (QMC), part of the University of Nottingham, regularly use heat maps as part of their study of the Limbal stem cells on the ocular surface of the eye.
“Compared to what is possible with modern data analysis software, previous studies were more complex to analyse and difficult for biologists to understand,” according to Dr Bina Kulkarni, one of the researchers working at QMC. “Data analysis is now much easier, as the latest software in this area provides instant graphical visualisation of the statistical tests in the form of heat maps, as well as variable and sample PCA plots, which really helps us to understand the analysis and the changes in gene expression patterns across different samples.”
What’s next? As computer technology improves – with greater processing power, better graphics applications and more sophisticated analysis software – data visualisation will continue to develop as well. As such, these new
methods of visualising data are likely to make traditional forms of data presentation (such as spreadsheets and basic graphics) obsolete in the future.
Epigenetic alterations Already, a team of scientists at the Institute of Human Genetics of the Christian-Albrechts-University in Kiel, Germany, is using data visualisation to support a number of national and international projects related to the epigenetic alterations related to several cancers, including malignant lymphoma, colorectal cancer, and hepatocellular carcinoma, as well as developmental disorders and other diseases.
“Larger studies, especially those which include multiple samples that need to be analysed on comprehensive array platforms, have traditionally been very time- consuming, and have also required a considerable amount of computer power,” says lead researcher Dr. Ole Ammerpohl. “As humans, we are all used to interpreting 3D pictures in our environment, and so our brain is able to find structures in complex 3D figures very quickly. Terefore, it’s no wonder that a 3D presentation of complex mathematical/statistical coherences makes its interpretation much easier for us.”
Even though the exploration and analysis of large data sets can be challenging, the use of tools like PCA and heat maps can provide a powerful way of identifying important structures and patterns very quickly, especially as visualisation typically provides the user with instant feedback, and with results that present themselves as they are being generated.
Already, the latest technological advances in this area are therefore making it much easier for scientists to compare the vast quantity of data generated by epigenetic studies and to test different hypotheses very quickly. As a result, the latest generation of data analysis software is helping scientists to regain control of this analysis, and to realise the true
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