How representative is an image

Many scientific publications, and especially those in the biological sciences, contain micrographs that are described in captions as 'representative images' or 'typical images'. Often, these claims are not accompanied by substantiating data, and there is seldom a requirement to provide the data as supplementary material. Poor experimental design and subconscious bias can lead to the publication of images that give a misleading impression to an otherwise objective study. We contend that the term 'representative image' can easily mislead the reader. Although it is mostly unintentional, it is unproductive. This chapter aims to highlight the issues leading to subjective selection and display of images. If objective criteria can be met, images are likely to provide meaningful content, and it is less likely that they will be dismissed as anecdotal evidence. It is recommended that author(s) aim to provide the reader with a true sense of the importance of the image in relation to the hypotheses and conclusions. 1. Is seeing really believing? What is a representative image? This chapter will explore what is meant by 'representative' with the intention of ensuring that visual data and their metrics have every possibility of being representative of a larger population. To illustrate this, we will explore the challenge of image selection, as well as sampling concepts and strategies. Our aim is to provide some universally applicable concepts, strategies and references that promote quantitative microscopy as opposed to descriptions of morphology. First, let us explore how this problem has arisen. Biologists have long been preoccupied with illustrative representations of classification criteria. Catalogues of new discoveries were described elegantly and skillfully using drawings and photographs, while whole branches of science evolved to deal with the resulting information. Systematics, taxonomy and nomenclature arose out of a need to make sense of the perceived order of Nature. Without order or the ability to extract and use it, databases are merely repositories of information, even though they might be comprehensive and worthwhile in the sense that they are available for future reference. Modern biology is less concerned with the discovery of new species but more the acquisition and interpretation of complex data in relation to normal function and disease. Databases of the modern Information Age are preoccupied with vast quantities of complex code; they require extensive effort to extract patterns and make sense of the complexity. The value of these databases is reliant on the ability to extract useful information for future reference, not merely as data deposition and storage repositories. In isolation, micrographs can be poor at describing Nature's complexity. Descriptive studies at the levels of cells and tissues are examples that do not lend themselves well to categorization. Organelles and cellular landscapes are highly pleomorphic, and they are subject to stochastic variability. We must accept that some of these systems are unique and might be representative only of the system from which they originated and at that particular instant in time. Although imaging of cells and tissues generates enormous quantities of data and associated metadata that contributes useful information, the selection of what will be published or even made available is highly problematic. On the other hand, the chemical and visual structures of individual proteins or supramolecular complexes have well- defined attributes (e.g. mass spectra, structural coordinates) that lend themselves to classification. Thus, while proteomics studies based on mass spectroscopy also generate huge amounts of data, it is recognized that selected data can be representative and valuable, provided that authors adhere to specific guidelines (1). This is also the case for structures in the Protein Data Bank where, again, guidelines and criteria exist for submission (http://www.rcsb.org/pdb/home/home.do). In specific cases and notably in the field of structural biology, very rigorous and systematic approaches are adopted by the microscopist. This is true for single-particle analysis of proteins and supramolecular complexes. It is also the case for 'visual proteomics' studies, which combine protein identity with in situ imaging (2,3). These approaches aim to provide statistically relevant conclusions that should be able to characterize an entire population of features with a known level of confidence. To some extent, they can even define and quantify heterogeneity.