Significance marker difference analysis(Multiple g





choosefile  example












Function introduction

1)T test was used to analyze the difference between the two groups of samples.The t-test is to use the t-distribution theory to infer the probability of differences,and to compare whether the difference between the two averages is significant.

2)Wilcoxon rank sum test was used to analyze the difference between the two groups of samples.The Wilcoxon rank sum test, also known as the Mann-Whitney U test, is a nonparametric test.Whether there is a significant difference in the distribution between test samples without the assumption that both sample spaces are normally distributed.

3)Add error bar to the column chart and a significantly different line between two samples

Input files

(1) Difference test form file: Enter the form file, the first column is the name of the different comparison group, each subsequent line is the data for each iteration of the comparison group.

(2) Repeat at least three times.

(3) Enter multiple sets of data for one sample at a time.

Parameter

(1) X-axis title: Enter the abscissa name.(The name can only be in English)

(2) Y-axis title: Enter the ordinate name.(The name can only be in English)

(3) Chart title: Enter the entire chart name.(The name can only be in English)

(4) Statistical test method selection: T test or rank sum test.

Results

Default output excel result table, histogram

Ttest.Pvalue. xls:T test result (parameter selection T test, output is T test result table).

wilcox.Pvalue. xls:Wilcoxon rank sum test result (parameter selection ank sum test, output is Wilcoxon rank sum test result table).

diff_stat.pdf/png:histogram.

1.Input file:

Input table file, must be TXT format.Optionally, open the data in excel and save it as "text file (TAB separated)(*.txt)".

Sample form: 

A

288.93

276.81

527.85

......

B

924.31

746.8

651.47

......

C

351.64

351.64

288.41

......

Difference test form

2. Result output:

compare p.format p.signif method
A-vs-B 0.023 * T-test
A-vs-C 0.722 ns T-test
B-vs-C 0.025 * T-test

The table rom left to right shows comparison group, P value, significance and analysis method .* stands for significance, and ns stands for no difference between groups.

 output graphics


Note: The abscissa is the name of the two comparison groups, and the ordinate is the average of the comparison group data. * represents significance,* represents two groups difference  less than 0.05 ,** represents two groups difference  less than 0.01,*** represents two groups difference  less than 0.001,and so on.