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Comparing Single Amino Acid Use

Hi all,

I have a question on comparison of single amino acid use in different classes. To be more clear, assume that there is 3 classes, named as C1 to C3, and i have ratios of each amino acid in that class (such as, in C1 there is approximately 40 protein and total of 8,345 amino acids, Gly has been observed 1,874 times, so 1874/8345= 22.5%, in C2 there is X protein, Y aminoacids and Gly has been observed Z times, in C3 goes like this....). How can i compare the single amino acid use among different classes in a statistically valid way, so in the end i can say that Gly has been over used in class 1 with p value<0.05 or something?

Thank you very much for your help!

statistics statistics statistics

2 answers

You could build a contingency table with 1 row per amino acid and 1 column per class.

Yes, but it will only help me to visualize the results, not determine the statistical significance, right?

Not at all. See in the the article linked: "The significance of the difference between the two proportions can be assessed with a variety of statistical tests including Pearson's chi-squared test, the G-test, Fisher's exact test, and Barnard's test, provided the entries in the table represent individuals randomly sampled from the population about which we want to draw a conclusion."

The Chi-squared test is a proper statistics for your case. It is usually used in place of the Fisher's exact test when you have a contingency table bigger than a 2x2. You should build up this contingency table the way fo3c suggested. Then you can import it in R for example, with a function like read.csv(). To run the test you need the function chisq.test(). Keep in mind that the Chi-squared test assume the independence of the observations.

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