# Quantifying Gene Chip Colors

When you get results for your Gene Chip exercise, you will need to match the color on your spots to the colors on these two charts. First, place your Gene Chip on a white surface or piece of paper. Then find which color matches the spots on your Gene Chip. You may have to estimate the color if yours falls in between the ones shown in these charts. For each spot, write down the ratio of experimental to control (X : C). However, keep in mind the chart below represents some of the colors from a continuous scale of colors, and therefore ratios. Your color might fall between two examples in this chart, so you'd need to select the ratio in between those displayed (e.g., 3:1).

Ratios of Transcription (Experimental : Control)

 <1:10 1:8 1:6 1:4 1:2 0:0 1:1 2:1 4:1 6:1 8:1 >10:1

Your goal is to match the color of the spot and not the intensity. In order to produce the Gene Chip simulation, we had to compromise in some technical aspects. Therefore, focus on the color and try to match it to the ratio of transcription scale above.

Now that you have converted the qualitative colors to quantitative data, you will need to perform some mathematical manipulations of your numerical data. The first step is to convert your ratios to single numbers. For example, 1:10 = 0.1 and 4:1 = 4.

The next step is to convert your single number ratios to log2-transformed numbers. Microarray data must be log-transformed in order to compare gene activities. Logarithms are exponents required to raise the base number (in our case 2) to a power in order to equal a desired number. For example, the logarithm of 8 using a base of 2 = 3 (23 = 8; log2 of 8 = 3). Log2 of 1/8 = -3 because log2 of 1/8 = log2 of 8-1 = 2-3. Remember that log2 of 2 = 1 and log2 of 1 = 0. Log2 of 0 is impossible to solve. Not all numbers are easily converted to logarithms (e.g., log2 of 3 = 1.6), so you may need to use a calculator.

Why log-transform microarray ratios?

What we want to be able to do is compare the change in transcription, or expression, for different genes. However, if we only use the ratios, it becomes difficult to compare directly. For example, consider the case below, where the expression levels of several genes are plotted over time:

In this example, all genes began at 1 fold, or baseline levels. Two genes have been highlighted in red. Which one changes its expression the most? From the graph, it appears that the upper gene did when it was transcribed 16 times more at 6 hours than at 0 hours. The bottom red gene went from 1.0 to approximately 0.1 which appears to be a minor change in transcription.

However, if all data are log2-transformed as shown below, you can discover that both genes changed their transcription levels by the same amplitude but in opposite directions. Remember that increased transcription of 16 = 24 which is equivalent to log2 of 4. Conversely, gene repression of 16 fold is equal to log2 of - 4 (1/16 = 16-1 = 2-4) . By log2-transforming the ratios (16 and 1/16), we can more easily measure the degree to which different genes alter their transcription.

One last point, when you want to compare expression levels of every gene in a genome, you should always log-transform your data. This will facilitate the calculation of genes with high similarity (i.e. correlation) of expression patterns.