Correlation analysis between groups

Select a file  Example

Select a file  Example

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The correlation coefficient of every two indexes between two tables.


(1)Tables can be data from different omics, like gene expression data, metabolite abundance data, microorganism abundance, or phenotype data, like indexes of height and weight.

(2)Each file should contains header information and column name. Each column represents sample, each row represents index like gene, OUT.

(3)File format: a tab delimited text file.

This tool will calculate the correlation coefficient between each row in the two files, ie the correlation between row data, like gene expression and metabolite abundance, environmental factors and OTU.


(1)Analysis type: define an analysis method, data can be analysed using pearson or spearman correlation coefficient

(2)Color (ascend from left to right):(white,green / white,blue /manually enter 2 colors/ green, white, red / blue, white, red/ manually enter 3 colors)(Default: white green)

(3)Frontsize:(Default: 10)

(4)Display numbers:(Default: no)

(5)Display cell border:(Default: no)

(6)Show the row name:(Default: yes)

(7)Show the column name:(Default: yes)


all.cor.matrix.xls:correlation coefficient This file can be used for drawing heatmap

all.pvalue.matrix.xls:p value matrix

all.cor_pvalue.list.xls:correlation coefficient list,This file can be used for drawing network graph in the Omicshare.(

all.cor_heatmap.png/pdf: A boxplot in PNG/PDF format

Result description:

Results interpretation: The positive number means positive correlation, the negtive number means negtive correlation.Generally standard for correlation degree:

Range of the coefficien Correlation degree
0.8-1.0 Extremely strong
0.6-0.8 Strong
0.4-0.6 Moderate
0.2-0.4 weak
0.0-0.2 Extremely weak or no

Generally standard for correlation significance: P value <0.05, significant; P value <0.01, extremely significant.


1、enter file1    enter file2   





all.pMatrix.xls: all.pMatrix.xls