Building on our previous work on the ALEA software package, a computational toolbox for allele-specific epigenomics analysis incorporating allelic variation data, we detail here ALEA’s successor - MEA. This package dramatically increases the functionality and usability of ALEA, incorporating allelic variation with existing resources, allowing for the identification of significant associations of epigenetic modifications and specific allelic variants in human and mouse cells. Similar to ALEA, MEA provides a customizable pipeline for allele-specific analysis of next-generation sequencing data which takes raw sequencing data for ChIP-seq, RNA-seq and DNA Methylation analysis, producing a UCSC track hub. MEA takes advantage of the available genomic resources for human (The 1000 Genomes Project Consortium) and mouse (The Mouse Genome Project) to reconstruct diploid in silico genomes for human samples or hybrid mouse samples. Then, for each accompanying ChIP-seq, RNA-seq or DNA Methylation dataset, MEA generates two wig files from short reads aligned differentially to each haplotype. This pipeline has been validated using human and hybrid mouse ChIPseq, RNAseq and DNA Methylation data (See Test Data).
- Docker installation
- distribution package
- documentation (PDF)
- test data: ftp://ftp.bcgsc.ca/supplementary/ALEA/files/test-data/
Hamid Younesy, Torsten Möller, Alireza Heravi-Moussavi, Jeffrey B. Cheng, Joseph F. Costello, Matthew C. Lorincz, Mohammad M. Karimi and Steven J. M. Jones, "ALEA: a toolbox for allele-specific epigenomics analysis." Bioinformatics 30.8 (2014): 1172-1174. [link to paper]
Julien Richard Albert, Tasuku Koike, Hamid Younesy, Richard Thompson, Aaron B. Bogutz, Mohammad M. Karimi and Matthew C. Lorincz, "Development and application of an integrated allele-specific pipeline for methylomic and epigenomic analysis (MEA)." BMC Genomics201819:463 (https://doi.org/10.1186/s12864-018-4835-2)