Shulou(Shulou.com)06/01 Report--

Today I will show you how to solve the two basic problems of Richness and Chao computing. The content of the article is good. Now I would like to share it with you. Friends who feel in need can understand it. I hope it will be helpful to you. Let's read it along with the editor's ideas.

Why can't 1.Richness and Chao be averaged?

For example, a sample square takes three samples as repetition. When calculating richness and Chao, many people calculate the three samples separately, get three values, and take an average as the richness and Chao of the sample.

But in fact, this is wrong!

The correct way is to add the OTU of the three samples, get and calculate the richness and Chao. In this way, the result is closest to the real value. It is precisely because of the requirements of the sum that there is no average, so naturally there is no error line and decimals.

However, in the statistical test, such as three samples from each of the two plots, test whether there is a significant difference in the number of species in the community between the two plots. In fact, three samples have to be counted as richness separately, so that a statistical test can be done.

Therefore, two different strategies are used in the calculation of richness and statistical test.

Further extrapolation, this problem exists for all alpha diversity indices, such as shannon, simpson and so on.

2. Chao is also related to sequencing depth, so why should Chao be calculated with raw data instead of resample data?

Chao is also related to the depth of sequencing, so we need to dig a hole and answer it later.

This is because the Chao obtained from the original data is closer to the real value. Although in principle, it is necessary to carry out resample first and eliminate the difference in sequencing depth between different samples before calculation can be comparable. But there is a bigger gap between the results and the real value. Therefore, it is possible that due to the great difference in sequencing depth between samples, the Chao obtained is also very different.

The core of the above two questions is how to calculate the value closer to the real value. In this way, sacrifices will be made elsewhere.

The first problem will be inaccurate in the statistical test, that is, in principle, it is impossible to test whether there is a significant difference in alpha diversity among different samples, because the alpha diversity calculated separately according to multiple samples in the sample square before the test is not accurate.

The second problem is that there are wrong results when comparing Chao between different samples. The level of Chao may be caused by the sequencing depth, not by the community itself.

These are all the contents of how to solve the two basic problems of Richness and Chao computing. For more content related to how to solve the two basic problems of Richness and Chao computing, you can search the previous articles or browse the following articles to learn! I believe the editor will add more knowledge to you. I hope you can support it!

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.