metascreen: A modular tool for the design and analysis of drug combination screens
Hanes, R.; Ayuda-Duran, P.; Ronneberg, L.; Zucknick, M.; Enserink, J. M.
Show abstract
There is a rapidly growing interest in high-throughput drug combination screening to identify synergizing drug interactions for treatment of various maladies, such as cancer and infectious disease. This creates the need for pipelines that can be used to design such screens, perform quality control on the data, and generate data files that can be analyzed by synergy-finding bioinformatics applications. metascreen is an open source, end-to-end modular tool available as an R-package for the design and analysis of drug combination screens. The tool allows for a customized build of pipelines through its modularity and provides a flexible approach to quality control and data analysis. metascreen is adaptable to various experimental requirements with an emphasis on precision medicine. It can be coupled to other R packages, such as bayesynergy, to identify synergistic and antagonistic drug interactions in cell lines or patient samples. metascreen is scalable and provides a complete solution for setting up drug sensitivity screens, read raw measurements and consolidate different datasets, perform various types of quality control, and analyze, report and visualize the results of drug sensitivity screens. Availability and implementationThe R-package and technical documentation is available at https://github.com/Enserink-lab; the R source code is publicly available at https://github.com/Enserink-lab/metascreen under GNU General Public License v3.0; bayesynergy is accessible at https://github.com/ocbe-uio/bayesynergy/ Selected modules will be available through Galaxy, an open-source platform for FAIR data analysis, Norway: https://usegalaxy.no
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- MAVEN: Compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny 93%
- Start&Stop - a PhysiCell and PhysiBoSS 2.0 add-on for interactive simulation control 93%
- Dashing Growth Curves - a web application for rapid and interactive analysis of microbial growth curves 92%
Similar papers in this journal
- ChemGenXplore: An Interactive Tool for Exploring and Analysing Chemical Genomic Data 94%
- WAVES (Web-based tool for Analysis and Visualization of Environmental Samples) – a web application for visualization of wastewater pathogen sequencing results 93%
- SGI: Automatic clinical subgroup identification in omics datasets 92%
Similar papers in this journal
- OCTAD: an open workplace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features 92%
- Optimizing the Cell Painting assay for image-based profiling 92%
- XomicsToModel: Multiomics data integration and generation of thermodynamically consistent metabolic models 91%
Similar papers in this journal
- HTSplotter: an end-to-end data processing, analysis and visualisation tool for chemical and genetic in vitro perturbation screening 94%
- The Image Data Explorer: interactive exploration of image-derived data 93%
- easyXpress: An R package to analyze and visualize high-throughput C. elegans microscopy data generated using CellProfiler 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.