Tool for integrative analysis of experimental proteomic data and genetics
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README.md

Genoppi v3.0

Genoppi is an interactive web application for analyzing and visualizing integrated experimental human proteomics data with genetics. It provides a visual interface for generating a variety of interactive plots to quality control raw data, integrate with GWAS dataset, identify known protein interacting partners, determine protein families present and offer easy visualization.

Installation

Genoppi requires R and RStudio. For best results, use the latest R version.
R is available at https://www.r-project.org/
RStudio is available at https://www.rstudio.com/products/rstudio/download/

Genoppi depends on several R packages. Run the following command from within RStudio to install them.

source("https://bioconductor.org/biocLite.R")
biocLite("limma")
install.packages(c("shiny", "shinyjs", "stringr", "VennDiagram", "rmarkdown", "plyr", "httpuv", "mime", "jsonlite", "xtable", "digest", 
                   "htmltools", "R6", "sourcetools", "ggplot2", "scales", "httr", "magrittr", "viridisLite", "base64enc", 
                   "htmlwidgets", "tidyr", "hexbin", "RColorBrewer", "dplyr", "tibble", "lazyeval", "crosstalk", "purrr", "data.table", "hash"))
install.packages("https://cran.r-project.org/src/contrib/plotly_4.7.1.tar.gz", repos=NULL, type="source")

Genoppi is stable using the following versions of each packages:

shiny 1.0.5
shinyjs 0.9
plotly 4.7.1
stringr 1.2.0
VennDiagram 1.6.17
rmarkdown 1.5
plyr 1.8.4
data.table 1.10.4
ggplot2 2.2.1
RColorBrewer 1.1-2

Running Genoppi

Genoppi can be 1. downloaded and ran locally or 2. run directly from Genoppi git repository.

  1. To modify the code to suit one's needs, the direct download link for Genoppi is https://github.com/lagelab/Genoppi/archive/master.zip

    To start local version of Genoppi, begin RStudio and run the following commands.

    library(shiny)
    runApp("/path/to/your/local/Genoppi/folder")
  2. Genoppi has frequent updates and to always have access to the latest code, running directly from the git repo is highly suggested.

    To run directly from Genoppi repository, YOU DO NOT NEED TO DOWNLOAD THE CODE. Begin RStudio and run the following commands.

    library(shiny)
    runGitHub("Genoppi", "lagelab")

Preparing your data

Human experimental proteomics data

Genoppi takes experimental IP-MS/MS results of bait pull down or full proteome data as text file. This file should include corresponding gene names or Uniprot accession numbers and either
(1) results of statistical analyses or
(2) values of logarithmic fold change (logFC, the ratio of case to control) for two replicates in chosen condition.

The headers must include
(1) gene, logFC, FDR, pvalue or
(2) gene, rep1, rep2
or
(1) accession_number, logFC, FDR, pvalue or
(2) accession_number, rep1, rep2

Any missing values in input files may lead to improper visualization of the data and thus will be removed.

Example files

Example dataset can be found in Genoppi/example.

Documentation and Support

Documentation may be accessed from within Genoppi interface using the "Documentation" tab.

Please address comments and questions to April Kim at aprilkim@broadinstitute.org, Edyta Malolepsza at edytam@broadinstitute.org or Kasper Lage at lage.kasper@mgh.harvard.edu.