CELLector: Genomics Guided Selection of Cancer in vitro models
Najgebauer, H., Yang, M., Francies, H., Stronach, E. A., Garnett, M. J., Saez-Rodriguez, J., & Iorio, F. (n.d.). CELLector: Genomics Guided Selection of Cancer in vitro Models. http://doi.org/10.1101/275032
2018-04-14 CELLector is a computational tool to assist the selection of the most relevant cancer cell lines to be included in a new in-vitro study (or to be considered in a retrospective study) in a genomic-guided fashion. CELLector combines methods from graph theory and market basket analysis; it leverages tumour genomics data to explore, rank, and select optimal cell line models in a user-friendly way, enabling scientists to make appropriate and informed choices about model inclusion/exclusion in retrospective analyses and future studies. Additionally, it allows the selection of models within user-defined contexts, for example, by focusing on genomic alterations occurring in biological pathways of interest or considering only predetermined sub-cohorts of cancer patients. Finally, CELLector identifies combinations of molecular alterations underlying disease subtypes currently lacking representative cell lines, providing guidance for the future development of new cancer models.
CELLector can be used in three different modalities:
(i) as an R package (within R, code available at: https://github.com/francescojm/CELLector)
(ii) as an online R shiny App (available at: http://ot-cellector.shiny.opentargets.io/CELLector_App/),
(iii) running the R shiny App locally (within Rstudio, code available at: https://github.com/francescojm/CELLector_App).
A tutorial on how to use the online Rshiny app (containing also instruction on how to run it locally) is available here: https://www.biorxiv.org/highwire/filestream/92891/field_highwire_adjunct_files/0/275032-1.pdf