Ongoing technological advances have driven increasing efficiencies and resolution to existing epigenomic measurements while enabling new dimensions of epigenomic analysis. Building on the vast amount of high-quality epigenomic datasets generated by IHEC members and other initiatives around the globe, the consortium has expanded its activities from data generation to increased integrative analyses and comprehensive data assessment.
Bringing together scientists from different research teams worldwide, the IHEC Integrative Analysis Working Group focuses on tools for epigenomic data analyses and the results of data integration projects. With the aim to further encourage and facilitate epigenomic data discovery and integrated epigenome interpretation, the group provides a forum to share and discuss new methods and tools that help advance our understanding of these highly complex and multi-dimensional datasets.
Take a look at selected papers published by members of the group, or browse the wide array of IHEC tools to analyse, navigate or interpret epigenomic data.
IHEC Data Portal
The IHEC Data Portal ensures data integration across the various IHEC research groups and is the central source to access and navigate IHEC data.
It allows epigenomic data integration, discovery, visualization, analysis, download, and sharing.
Selected Publications by Members of the Integrative Analysis Working Group
eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data
Author(s): Breeze, C. E., Reynolds, A.P., van Dongen, J., Dunham, I., Lazar, J., Neph, S., Vierstra, J., Bourque, G., Teschendorff, A. E., Stamatoyannopoulos, J. A., Beck, S.Reference: Bioinformatics, 2019 Jun 4. pii: btz456. doi: 10.1093/bioinformatics/btz456
gemBS: high throughput processing for DNA methylation data from bisulfite sequencing
Author(s): Merkel, A., Fernández-Callejo, M., Casals, E., Marco-Sola, S., Schuyler, R., Gut, I. G., Heath, S. C.Reference: Bioinformatics, Volume 35, Issue 5, 01 March 2019, Pages 737–742, doi: 10.1093/bioinformatics/bty690
The epiGenomic Efficient Correlator (epiGeEC) tool allows fast comparison of user datasets with thousands of public epigenomic datasets.
Author(s): Laperle, J., Hébert-Deschamps, S., Raby, J., de Lima Morais, D. A., Barrette, M., Bujold, D., Bastin, C., Robert, M.-A., Nadeau, J.-F., Harel, M., Nordell-Markovits, A., Veilleux, A., Bourque, G., Jacques, P.-E.Reference: Bioinformatics, Volume 35, Issue 4, 15 February 2019, Pages 674–676, doi: 10.1093/bioinformatics/bty655
High-resolution TADs reveal DNA sequences underlying genome organization in flies
Author(s): Ramírez, F., Bhardwaj, V., Arrigoni, L., Lam, K.C., Grüning, B. A., Villaveces, J., Habermann, B., Akhtar, A., Manke, T.Reference: Nature Communications, Volume 9, Article number:189 (2018), doi: 10.1038/s41467-017-02525-w
Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning
Author(s): Hocking, T. D., Goerner-Potvin, P., Morin, A., Shao, X., Pastinen, T., Bourque, G.Reference: Bioinformatics, Volume 33, Issue 4, 15 February 2017, Pages 491–499, doi: 10.1093/bioinformatics/btw672
The International Human Epigenome Consortium Data Portal
Author(s): Bujold, D., de Lima Morais, D. A., Gauthier, C., Côté, C., Caron, M., Kwan, T., Chen, K. C., Laperle, J., Markovits, A. N., Pastinen, T., Caron, B., Veilleux, A., Jacques, P.-E., Bourque, G.Reference: Cell Systems, Volume 3, Issue 5, 23 November 2016, Pages 496-499, doi: 10.1016/j.cels.2016.10.019
Should you have any questions or wish to get in touch with the group, please contact the Integrative Analysis Working Group Chairs.