Hi I did an experiment for miRNA and targets but I have a problem in calculating the significance of the data can you help me which test should I have to use and how to caluclte the p value or z score for these data
negative (no vector)
Positive ( null miRNA vector + gene)
G1, G2, G3 (miRNA vector + gene)
Dear Marwa, The correct approach to the analysis of your data - and any other, for that matter - is to state your Null Hypothesis first. In other words, what is your goal? Presumably, you mean to show that two events are the same or not. You must make this clear. The way you stated your question reads "Here are data, now help me find a test". Not appropriate. What you want to say is "I want to show that ... is true (e.g., equal means, equal medians, equal variances, etc) under the given experimental conditions". Furthermore, with stating your hypothesis, you make a choice regarding the significance cut-off. Usually, at 5% (or 0.05). You may not realize it, but by stating your hypothesis, you have defined "your" test statistic - in advance, mind you, and without having gathered data. Then, you go gather data, apply the test statistic and state whether under the conditions given, you accept or reject the hypothesis. In summary, your problem is that you do not state what you wanted to discover from the data. Please do so - essential for you, and essential for those who are willing to help you with your question. Best regards, Hans
Dr Hans thanks for your clarification you're right now I corrected it. My null hypothesis is that the control have significant increase in the expression of luciferase in comparison with their genes but I don't know which test should I have to use and how. I know it's non-parametric one but I don't know which one and how to do it.
Dear Marwa,
Good! However, you should be careful with the word "controls". "Control" means to express the state of an unperturbed system (also sometimes called "normal"). The behavior of the perturbed system is compared to that recorded for the control. The next step is to key in on the patterns that you can discern from your data. You calculated the ratios F/R. As you read along this column, you find ratios close to 1 for specific groups of experiments versus ratios closer to 0 for other groups of experiments. I do not know the exact context of your experiments, so I take a possibly simplistic approach by saying "Let's just see how the two medians compare" (medians Gi, medians "pos Gi"). John Tuckey called this approach "exploratory data analysis" and it is often enough to clarify the situation. You may not wish to use the F/R ratio, but simply work with F and R values directly: = versus != ; or equivalently, = 0 v. !=0. Long story short, give Kruskal-Wallis a shot (take a look at: http://support.minitab.com/en-us/minitab/17/topic-library/basic-statistics-and-graphs/hypothesis-tests/nonparametrics-tests/why-use-kruskal-wallis/). As for software, I fancy R. I believe that you can do this test in Excel. A better alternative for you should be "InStat" by GraphPad (http://www.graphpad.com/scientific-software/instat/), as it guides you through an analysis and comments its outputs really well. Sorry for the long message.
Best, Hans
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