Bioinformatics Development & Statistical Genomics

The research focus of the team is on the development and application of efficient methods (from both statistical and computational perspectives) for the large-scale processing and integrative analysis of omics datasets. These methods have been developed into analysis pipelines, and have been applied to both in house and collaborative projects (notably with the International Human Epigenome Consortium, IHEC).  The largest dataset we are currently working on is from the IBD-CHARACTER project.  This is a large multi-omics dataset from patients with Inflammatory Bowel Disease (IBD), consisting of expression, DNA-methylation and microbiome data on tissue biopsies from inflamed and non-inflamed gut tissue.  We are also re-analysing WGBS (DNA methylation) datasets from TCGA and ICGC in the context of the Pan Cancer project to enable investigation of common epigenetic signatures across different cancer types.

The team also has a production focus in the processing, analysis and interpretation of epigenetic datasets (mostly DNA methylation studies from WGBS experiments).

• Further improvements to GemBS, our WGBS analysis pipeline, to improve efficiency, accuracy and portability.  Containerized versions (Docker and Singularity) have been made publically available.  GemBS has been adopted as the standard IHEC pipeline for WGBS analysis, and we are working with ENCODE towards their adoption of GemBS as a standard pipeline.
• Active participation in the IHEC assay standards committee to determine minimum reporting standards for WGBS analyses, which have been implemented into GEMBS.
• Develop methods for predicting chromatin domains from individual DNA methylation datasets (from both sequence and microarray platforms) without requiring reference datasets.  This allows rapid prediction of domains in the wide set of samples for which array or sequence based methylation datasets are available.
• Continue characterization of partially methylated domains across cell types during differentiation and oncogenesis.
• Integrative analysis of IBD-CHARACTER multi-omics dataset with the aim of identifying epigenetic signatures of disease from the tissue biopsies.

Beekman R, Chapaprieta V, Russiñol N, Vilarrasa-Blasi R, Verdaguer-Dot N, Martens JHA, Duran-Ferrer M, Kulis M, Serra F, Javierre BM, Wingett SW, Clot G, Queirós AC, Castellano G, Blanc J, Gut M, Merkel A, Heath S, Vlasova A, Ullrich S, Palumbo E, Enjuanes A, Martín-García D, Beà S, Pinyol M, Aymerich M, Royo R, Puiggros M, Torrents D, Datta A, Lowy E, Kostadima M, Roller M, Clarke L, Flicek P, Agirre X, Prosper F, Baumann T, Delgado J, López-Guillermo A, Fraser P, Yaspo ML, Guigó R, Siebert R, Martí-Renom MA, Puente XS, López-Otín C, Gut I, Stunnenberg HG, Campo E, Martin-Subero JI.
“The reference epigenome and regulatory chromatin landscape of chronic lymphocytic leukemia.”
Nat Med, 24(6):868-880, 2018. doi: 10.1038/s41591-018-0028-4.

Grassi L, Pourfarzad F, Ullrich S, Merkel A, Were F, Carrillo-de-Santa-Pau E, Yi G, Hiemstra IH, Tool ATJ, Mul E, Perner J, Janssen-Megens E, Berentsen K, Kerstens H, Habibi E, Gut M, Yaspo ML, Linser M, Lowy E, Datta A, Clarke L, Flicek P, Vingron M, Roos D, van den Berg TK, Heath S, Rico D, Frontini M, Kostadima M, Gut I, Valencia A, Ouwehand WH, Stunnenberg HG, Martens JHA, Kuijpers TW.
“Dynamics of Transcription Regulation in Human Bone Marrow Myeloid Differentiation to Mature Blood Neutrophils.”
Cell Rep, 24(10):2784-2794, 2018. doi: 10.1016/j.celrep.2018.08.018.

Singh AA, Petraglia F, Nebbioso A, Yi G, Conte M, Valente S, Mandoli A, Scisciola L, Lindeboom R, Kerstens H, Janssen-Megens EM, Pourfarzad F, Habibi E, Berentsen K, Kim B, Logie C, Heath S, Wierenga ATJ, Clarke L, Flicek P, Jansen JH, Kuijpers T, Yaspo ML, Valle VD, Bernard O, Gut I, Vellenga E, Stunnenberg HG, Mai A, Altucci L, Martens JHA.
“Multi-omics profiling reveals a distinctive epigenome signature for high-risk acute promyelocytic leukemia.”
Oncotarget, 9(39):25647-25660, 2018. doi: 10.18632/oncotarget.25429. 

Stefanini I, Rizzetto L, Rivero D, Carbonell S, Gut M, Heath S, Gut IG, Trabocchi A, Guarna A, Ben Ghazzi N, Bowyer P, Kapushesky M, Cavalieri D.
“Deciphering the mechanism of action of 089, a compound impairing the fungal cell cycle.”
Sci Rep, 8(1):5964, 2018. doi: 10.1038/s41598-018-24341-y.

Esteve-Codina, A.
“RNA-Seq Data Analysis, Applications and Challenges.”
In Data Analysis for Omic Sciences: Methods and Applications, 82:71, 2018.

Merkel, A. & Heath, S.C.
“DNA Methylation Assays Using Bisulphite Sequencing and Next-Generation Sequencing.”
In Data Analysis for Omic Sciences: Methods and Applications, 82:107, 2018.