Figures are one of the most difficult sections to prepare because they are so many different possibilities and options available and there is no right or wrong way to present your data. You have to find the type of figure that can best present your specific results. Note that contrary to the tables, the figure legends are placed below the graphs, and figures are commonly read from bottom to top. Each figure should fill about half a page. You have the option to use colors, but if you do, you will usually be charged for it. I recommend you use black and white because you can play with different grey intensities and it will reproduced better on photocopies. Also, use colors only if the color is necessary for the understanding of the graph, and not just for esthetics.
As you can see on the example below, figures do not have a title like tables do, but instead have a legend. The figure legends must be reported on a separate page within your manuscript, between the reference list and the tables, and not on the figure directly. In the legend, explain carefully what is presented and how. You can also include information on the conditions of the experiment, etc.
When there are multiple graphs that relate to the same experiment, or a group of related experiments, present them as a compound figure. Compound figures are multiple graphs integrated into a single figure that share a common legend. Each subfigure is then identified by capital letters such as A, B, C. When you refer to a figure in the results, be sure to include the letter (e.g. Fig. 2A). The compound figure legend should then include the legend for the overall figure, as well as for each individual graph.
Four common types of figures are:
- Bar graphs that are used to compare a single variable value between several groups, for example to present the mean protein concentration levels of a group of patients and a group of controls.
- Frequency histograms that are often called frequency distributions graphs. These can be used to show how a measured category is distributed along a measured variable. These graphs are typically used for example to check if a variable follows a normal distribution, such as the distribution of protein levels between different individuals of a population.
- X,Y scatterplot that are used to show the relationship between two variables and if their value change in a consistent way, for example if you want to check the relationship between the concentration levels of two different proteins.
- X,Y line graph that plot a series of related values that depict a change in Y as a function of X, for example to present a dose-response curve showing the effect of increasing doses of a treatment.
A few other tips to remember about figures:
- The units are presented on the axis labels.
- The main variable measured is presented on the Y axis.
- The categories are presented on the X axis.
- The colors must be defined and can be used to present a second categorical variable.
- Statistically significant differences can be presented by adding stars on the graph or by adding directly the p-values like in the example above (in this case, explain the statistical measures in the legend).
- Present error bars when necessary.
- Adapt the axis to decrease the waste of blank space in the graphs.
- Connect the dots if each point in the series is obtained from the same source and is dependent on the previous values (e.g. a plot of a baby’s weight over the course of a year).
- Use different symbols for each treatment and make them large enough so that they can be easily read on the graph.