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How to understand the data in the GEO database difference analysis tool GEO2R, many novices are not very clear about this, in order to help you solve this problem, the following editor will explain in detail for you, people with this need can come to learn, I hope you can get something.

The data in the GEO database is open, and many researchers will download the data to analyze it themselves, in which differential expression analysis is one of the most common analysis strategies. In order to facilitate you to better mine the data in GEO, the official website provides a tool GEO2R, which can analyze differences conveniently.

GEOquery

Limma

GEOquery is used to automatically download GEO data and read it into R environment; limma is a classic difference analysis software used to perform difference analysis.

A set of samples is represented by series in the GEO database, such as GSE25724, which contains two groups of case and control. The case group contains 6 biological repeats, and the control group contains 7 biological repeats, a total of 13 samples. The link is as follows

Https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE25724

You can see the button of GEO2R on the web page, and click this button to analyze it. In addition to difference analysis, GEO2R also provides some simple data visualization functions.

1. Value distribution

This option uses a box chart to show the distribution of expression in all samples, and the results are as follows

2. Profile graph

This option is used to show the distribution of a probe / gene in all samples, and the results are as follows

Click Sample values to see the corresponding expression value, as shown below

The steps for GEO2R to analyze the differences are as follows

1. Define sample grouping

Define the sample group through the Define groups button, first enter a name of group, and then select the corresponding sample, as shown below

two。 Parameter adjustment

Through the Options menu at the bottom of the page, you can adjust the parameters for difference analysis, as shown below

The first parameter is used to select the P-value correction algorithm for multiple hypothesis testing, the second parameter indicates whether to perform log conversion on the original expression, and the third parameter adjusts the corresponding platfrom annotation information shown in the final result, whether it is based on the information in the supplement file provided by the customer or using the information in the soft file.

3. Execution

Click the Top 250 button shown below to perform the difference analysis.

The results are shown below, showing only the 250 most significant differential genes on the page.

The results of all genes can be derived through Save all results, and the difference analysis can be completed sequentially without any programming basis through GEO2R.

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