You can download the paper at F1000Research and cite the paper:
- Yang Z, Pandey P, Marjoram P and Siegmund KD. iMutSig: a web application to identify the most similar mutational signature using shiny [version 2; peer review: 2 approved]. F1000Research 2020, 9:586 (https://doi.org/10.12688/f1000research.24435.2)
This Shiny app is hosted at shinyapps.io where you can access using the link https://zhiyang.shinyapps.io/imutsig/.
If you'd like to use this Shiny app locally, please type the following command in your RStudio.
git clone https://github.com/USCbiostats/iMutSig.git
To run the Shiny app, you need to install the following packages. If you run into any issues while installing pmsignature
, please refer to its GitHub page for more details https://github.com/friend1ws/pmsignature.
packages <- c("shinyjs", "shinydashboard", "shiny", "dplyr",
"DT", "corrplot", "stringr", "devtools")
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
install.packages(setdiff(packages, rownames(installed.packages())))
}
if (!("d3heatmap" %in% rownames(installed.packages()))){
devtools::install_github("rstudio/d3heatmap")
}
if (!("pmsignature" %in% rownames(installed.packages()))){
devtools::install_github("friend1ws/pmsignature", ref = "devel")
}
if (!("decompTumor2Sig" %in% rownames(installed.packages()))){
devtools::install_github("zhiiiyang/decompTumor2Sig")
}
By clicking the Run App
button in either ui.R
or server.R
script, a Shiny app will run locally. Or you can simply enter runApp()
in the console.
Please open an issue at https://github.com/USCbiostats/iMutSig/issues if you run into any issues or would like to add a new feature. Thank you!
This work was supported by NCI grant numbers 5P30 CA014089 and P01 CA196569.