iCKI

Individualized co-expression-like index

Software / iCKI v1.0 (Java)

Introduction

iCKI v1.0 (Java) has the following main functions.

1、Calculate the individual co-expression-like index (iCKI) for each individual.
2、Perform the DC (differential co-expression) analysis framework to accurately detect the co-expression changes under differential conditions.

Note: The two functions are implemented by one command line.


Pre-installation

iCKI v1.0 (Java) is implemented by Java. Before using it, please install Java programing environment (Java 8 or update) first.


Download

iCKI v1.0 (Java, Command-line running)


Usage

command-line example:


java -jar iCKI.jar -DC.test -input.factor_1 gene_1.txt -input.factor_0 gene_0.txt -output.ICI_1 iCKI_1.txt -output.ICI_0 iCKI_0.txt -output.DC_test DC_test_result.txt


parameters:

-DC.test: Perform the DC analysis;
-input.factor_1: Input the biomarker information (eg.gene expression) of the case group;
-input.factor_0: Input the biomarker information (eg.gene expression) of the control group;
-output.ICI_1: Specify the file name of the iCKI values of the co-expression pairs of all samples in the case group;
-output.ICI_0: Specify the file name of the iCKI values of the co-expression pairs of all samples in the control group;
-output.DC_test: Specify the file name of the results of DC test.

Input file

please see gene_1.txt and gene_0.txt for more information

column 1: (e.g. marker1) is the ID or name of the biomarker.

column 2 to the last are the biomarker information of each sample.

Output iCKI file

please see iCKI_1.txt and iCKI_0.txt for more information

column 1: (e.g. marker1_marker18) is the name of co-expression pair.

column 2 to the last are iCKI values of each sample.

Output DC analysis results

please see DC_test_result.txt for more information

It contains 18 columns:

markerI_markerII -> the name of co-expression pair;
change_type -> change type of co-expression;
dx1_x0 -> the mean difference between case and control groups;
Sx1_x0 -> the standard error between case and control groups;
df -> the degree of freedom;
ICI_mean_1 -> the average iCKI in the case group;
ICI_mean_0 -> the average iCKI in the control group;
sample_num_1 -> the sample size of the case group;
sample_num_0 -> the sample size of the control group;
fold_change -> the fold change value;
t -> the DC statistics;
tp -> the p value.


The simulated data and results were offered to test: Download