Signal: The home page of mutational signatures

Abstract

Abstract Background The somatic mutations found through sequencing a whole tumour genome are the aggregate outcome of one or multiple mutational processes. Each of these processes leaves a characteristic imprint, or mutational signature, on the genome. The final mutational profile is determined by the pattern of exposure of each of these mutational processes. Deconstructing the signature composition of a tumour’s mutational profile provides insights into the biological processes that drive it. The initial research in this field extracted 5 substitution signatures from 21 breast cancer samples, but research since has extracted signatures from ever expanding datasets of whole tumour genomes and experimental mutagenesis systems. Signatures have also been developed for different mutation types. The field has great potential to aid in the diagnosis and treatment of cancer patients. Methods We developed a website using the ReactJS framework supported by a distributed compute cluster in OpenStack. Results Here we present Signal, a new website enabling exploration of the latest research in the field of mutational signatures. With Signal we intend to inform the scientific community of the power of mutational signatures and to provide the results of our research in a dynamic, easy-to-use interface. This includes tissue-specific substitution and rearrangement signatures extracted from the PanCan dataset, in addition to signatures extracted from cell-lines exposed to environmental mutagens and gene-knockouts. Users can upload their own variant calls for analysis by our pipeline, which will filter out kataegis regions, construct a substitution profile and detect the presence of any of our gold-standard substitution signatures. This signature fitting algorithm leverages the organ-specificity of our new signature extraction framework, leading to more accurate signature predictions than previously possible. Conclusions We intend for Signal to be the home page of mutational signatures which will be kept at the forefront of research with the most recent published data and analysis methodologies. Legal entity responsible for the study The authors. Funding CRUK. Disclosure All authors have declared no conflicts of interest.