Private project files, including a modified version of metaCCA.

• Bugs fixed relating to single-study analysis

Key Information:

• The README.txt files in each folder explain what should be in each folder
• Large files that cannot be contained in the REPO must be obtained seperately, which mainly includes 1000GP data, GWAS-ATLAS data, and S_XY files.
• The only files which need to be created/edited manually are:
  • S_XY_ATLAS-xxxx.txt (reformat GWAS-ATLAS data)
  • POP-Lists/*.txt (download & reformat)
  • SNP-Lists/*.txt (download & reformat; or created otherwise)
• The files which can be created semi-automatically using MATLAB scripts inlcude:
  • S_XX_ATLAS-xxxx.txt (estimateSxx.m)
  • Data_SNPs/*.txt (get_snpdata.m)
  • Results/*.txt (TEST_RUN.m, Multi_SNP_TEST.m, etc)
• For univariate SNP analysis, only S_XY is needed
• For multivariate SNP analysis
  • POP-Lists, SNP-Lists are used to generate Data_SNPs
  • Data_SNPs/*.txt are used to generate S_XX
  • S_XY, S_XX, SNP-Lists are used to generate Results

Original metaCCA README:

The MATLAB codes in this repository can be used to perform metaCCA
(and its variant metaCCA+) - summary statistics-based analysis
of a single or multiple genome-wide association studies (GWAS)
that allows multivariate representation of both genotype and phenotype.

example.m demonstrates the usage of metaCCA. Test files are provided.

Please cite the following paper when using the software:
metaCCA: Summary statistics-based multivariate meta-analysis
of genome-wide association studies using canonical correlation analysis.

15/07/2015 Anna Cichonska, [email protected]

R implementation: http://bioconductor.org/packages/metaCCA/