GEDA (Gene Expression & Drug Activity in Cancer Cells: Robuts Correlations & Networks) is a web tool developed in R-shiny to plot Gene expression versus Drug activity in different cell lines grouped by tissues. GEDA uses Pearson & Spearman correlation to put forth gene & drug interaction grouped by tissues in two different drug datasets (FDA and Non-FDA approved), further evaluated by the p-value of each correlation.
GEDA is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

R packages used

[1] W. Chang, J. Cheng, J. Allaire, et al. shiny: Web Application Framework for R. R package version 1.4.0. 2019. <URL: https://CRAN.R-project.org/package=shiny>.

[2] M. Dowle and A. Srinivasan. data.table: Extension of data.frame. R package version 1.12.2. 2019. <URL: https://CRAN.R-project.org/package=data.table>.

[3] V. Perrier, F. Meyer, and D. Granjon. shinyWidgets: Custom Inputs Widgets for Shiny. R package version 0.4.8. 2019. <URL: https://CRAN.R-project.org/package=shinyWidgets>.

[4] T. Rinker and D. Kurkiewicz. pacman: Package Management Tool. R package version 0.5.1. 2019. <URL: https://CRAN.R-project.org/package=pacman>.

[5] P. Solymos and Z. Zawadzki. pbapply: Adding Progress Bar to ’apply’ Functions. R package version 1.4-1. 2019. <URL: https://CRAN.R-project.org/package=pbapply>.

[6] H. Wickham, W. Chang, L. Henry, et al. ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. R package version 3.2.1. 2019. <URL: https://CRAN.R-project.org/package=ggplot2>.

[7] H. Wickham, R. François, L. Henry, et al. dplyr: A Grammar of Data Manipulation. R package version 0.8.3. 2019. <URL: https://CRAN.R-project.org/package=dplyr>.

[8] Y. Xie, J. Cheng, and X. Tan. DT: A Wrapper of the JavaScript Library ‘DataTables’. R package version 0.8. 2019. <URL: https://CRAN.R-project.org/package=DT>.

[9] G. Yu. shadowtext: Shadow Text Grob and Layer. R package version 0.0.5. 2019. <URL: https://CRAN.R-project.org/package=shadowtext>.

[10] D. Attali and T. Edwards. shinyalert: Easily Create Pretty Popup Messages (Modals) in ‘Shiny’. R package version 1.0. 2018. <URL: https://CRAN.R-project.org/package=shinyalert>.

[11] S. Garnier. viridis: Default Color Maps from ‘matplotlib’. R package version 0.5.1. 2018. <URL: https://CRAN.R-project.org/package=viridis>.

[12] H. Wickham. reshape: Flexibly Reshape Data. R package version 0.8.8. 2018. <URL: https://CRAN.R-project.org/package=reshape>.

[13] B. Auguie. gridExtra: Miscellaneous Functions for “Grid” Graphics. R package version 2.3. 2017. <URL: https://CRAN.R-project.org/package=gridExtra>.

[14] A. Sali. shinycssloaders: Add CSS Loading Animations to ‘shiny’ Outputs. R package version 0.2.0. 2017. <URL: https://CRAN.R-project.org/package=shinycssloaders>.

[15] H. Wickham. tidyverse: Easily Install and Load the ‘Tidyverse’. R package version 1.2.1. 2017. <URL: https://CRAN.R-project.org/package=tidyverse>.

References

- Presented in X Int. Conf. on Bioinformatics SoIBio Conference 2019 Montevideo, URUGUAY. Seeking new target candidates in cancer: Analysis of the correlation of Oncogene expression with Drug activity. ST: Mónica M. Arroyo. Pontifical Catholic University of Puerto Rico (PCUPR), Ponce, Puerto Rico.
- Monica M Arroyo, Alberto Berral-Gonzalez, Santiago Bueno-Fortes, Diego Alonso-Lopez, Javier De Las Rivas. Discovery of new drug-target candidates in cancer: analysis of correlation of cancer gene expression with drug activity. Biomolecules. Submitted for Publication .

About us

The Bioinformatics and Functional Genomics Research Group is located in the Cancer Research Center (CiC-IBMCC, CSIC/USAL/IBSAL) Salamanca (SPAIN) directed by Dr. Javier De Las Rivas. Our research is driven by the integrative analyses of genomic and proteomic data derived from patient-oriented studies in cancer. Using bioinformatics applied to find new cancer biomarkers and cancer drivers, cancer genomic data to improve patient stratification, disease subtype profiling and prognosis analysis, computational Biology and Bioinformatics applied to studies in onco-hematology and studies on the human proteome and interactome: build, validate and analyse protein interaction networks.

GEDA v 1.0.0.

Browsers tested: Chrome ( v.80 & v.76), Firefox (v.72 & v.66), Opera( v.66 & v.60), Safari(v.12, v.11 & v10.1), Internet Explorer(v.11, v.10 & v.8)

Tested in:

• macOS
• High Sierra
• Mojave
• Sierra
• Windows
• 10
• 8.1
• 8
• 7
• XP
• Linux
• Ubuntu 18.04