Correlation analysis within group





Select a file  Example

















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Function:
The correlation coefficient and p values are calculated to evaluate the correlation direction, degree and significance within group.


Input:

(1)The table contains analysing data and header information. In the example file, the header is name of samples, the column name is gene ID, each row data are expression FPKM value of certain gene in each samples.

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


Parameters:

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

(2)Vector for analysis: define vector for analysis. In the example file, selecting column vector means calculating correlation coefficient between samples, which can be used for evaluation of sample repeatability and difference; while row vector means correlation between genes, which can be used for regulation analysis between gene expression.

(3)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)

(4)Frontsize:(Default: 10)

(5)Display numbers:(Default: no)

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

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

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


Output:

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.(http://www.omicshare.com/tools/Home/Soft/cytoscape)


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.

example :

1、Input filefilecor.txt   

2、Parameters


Output:


all.pearson.xls:all.pearson.xls


all.corMatrix.xls:all.corMatrix.xls


all.pMatrix.xls: all.pMatrix.xls


all.cor_heatmap.png/pdf

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