Recent advances in molecular biology, Bioinformatics techniques have brought to an explosion of the information about the spatial organisation of the DNA inside the nucleus. In particular, 3C-based techniques are revealing the genome folding for many different cell types,, permit to create a more effective representation of the disposition of genes in the three-dimensional space. This information can be used to re-interpret heterogeneous genomic data (multi-omic) relying on 3D maps of the chromosome. The storage, computational requirements needed to accomplish such operations on raw sequenced data have to be fulfilled using HPC solutions,, the the Cloud paradigm is a valuable, convenient mean for delivering HPC to Bioinformatics. In this work we describe a data analysis work-flow that allows the integration, the interpretation of multi-omic data on a sort of "topographical" nuclear map, capable of representing the effective disposition of genes in a graph-based representation. We propose a cloud-based task farm pattern to orchestrate the services needed to accomplish genomic data analysis, where each service represents a special-purpose tool, playing a part in well known data analysis pipelines.