RE2C

• RE2C is a free, open-source meta-analysis software tool for genome-wide association study analysis, designed to perform both basic and advanced meta-analytic methods in an efficient manner. RE2C allows users to test heterogeneous effect size between individual statistics by using an optimization technique, spectral decomposition. Our optimization procedure is fast and robust and takes only a day for 1 000 000 SNPs.

Getting Started

In order to download RE2C, you should clone this repository via the command

git clone git://github.com/cuelee/RE2C.git
cd RE2C

Updating RE2C

You can update to the newest version of RE2C using git. First, navigate to your RE2C/ directory, then run

git pull

User Guide

• Usage Command line arguments: bash RE2C.bash

Option	Description
--i [FILE]	Input file (Required)
--o [FILE]	Output file (default=./out.txt)
--c [FILE] or --cor [FILE]	Correlation matrix
--threads [N]	Use multi-thread computing (default=1)
--h or --help	Print help

• Input File Format

  • Each rows represent a SNPs.

    • The first column of each rows is for rsID, and the following columns are pairs of effect size and its standard error of Nth study. (If we meta-analyze 5 summary statistics then each line must have 11 columns)

  • Correlation matrix is N x N symmetric matrix.

    • An evaluated correlation matrix can be specified by using --cor option in RE2C. When --cor is unused, the code itself assumes an identity matrix of N rows and columns.

Example (Input File)

rsAAAAAA study1beta study1stderr study2beta study2stderr study3beta study3stderr
rsBBBBBB study1beta study1stderr study2beta study2stderr study3beta study3stderr
rsCCCCCC study1beta study1stderr study2beta study2stderr study3beta study3stderr

• Example (Correlation Matrix)

C1	C2	C3	C4
1	a	b	c
a	1	d	e
b	d	1	h
c	e	h	1

• Example Run

bash RE2C.sh --input ./example/example_input.txt --output ./out --cor ./example/example_cor.txt

• Output File

Col. Num.	Col. name	Description
1	rsID	SNP rsID
2	Nstudy	Number of studies used in meta-analysis
3	LSp	Lin-Sullivan’s P-value (FE)
4	RE2Cs1	RE2C statistic mean effect part
5	RE2Cs2	RE2C statistic heterogeneity part
6	RE2Cp	RE2C p-value
7	RE2Cp*	RE2C* p-value

RE2C generates two statistical significances: RE2Cp and RE2Cp*. which one should I use for my analysis?

The original RE2C model (RE2Cp) was developed to complement the FE model, the golden standard in meta-analysis. For example, Let assume that we ran association tests on a SNP using 1. the conventional fixed effect meta-analysis, and 2. RE2C. If the p-value of the fixed effect method (LSp) is 0.03 and the p-value of the RE2C model (RE2Cp) is 0.01, the statistical significance of this SNP will be of min(0.03, 0.01) * 2 = 0.02.

We later discovered that some might just want to use the statistical significance of RE2C alone. In this case, you can use RE2Cp* (not RE2Cp).

Citation

If you use our software or refer to the RE2C method, please cite. Lee CH, Eskin E, Han B. Increasing the power of meta-analysis of genome-wide association studies to detect heterogeneous effects. Bioinformatics. 2017;33(14):i379–88.

Support

Issues with RE2C? Email cuelee@snu.ac.kr

License

gnu license 3.0

Authors

Cue Hyunkyu Lee ( Seoul National University )

Funding Information

C.H.L B.H are supported by a grant of the Korean Health Technology R&D project, Ministry of Health & Welfare, Republic of Korea (Hl14C1731).