Eatomics

Eatomics is an R-Shiny based web application that enables interactive exploration of quantitative proteomics data generated by MaxQuant software. Eatomics enables fast exploration of differential expression and pathway analysis to researchers with limited bioinformatics knowledge. The application aids in quality control of the quantitative proteomics data, visualization, differential expression and pathway analysis. Highlights of the application are an extensive experimental setup module, the data and report generation feature and the multiple ways to interact and customize the analysis.

Getting started

1. Install R and Rstudio

If you do not have installed R and Rstudio yet, please find the installation procedure for your distribution at https://rstudio.com/products/rstudio/download/.

2. Run Shiny App in Rstudio

Within R studio please run

install.packages("shiny")
install.packages("devtools")

library(shiny)
library(devtools)

devtools::install_github('sfirke/janitor')

runUrl("https://github.com/Millchmaedchen/Eatomics/archive/master.zip", subdir = "R")

3. Input Files

1. Demo_proteinGroups.txt: The proteinGroups.txt (i.e. a tab-separated files) as generated by the quantitative analysis software of raw mass spectrometry data - MaxQuant. The file should contain at least the columns Protein IDs, Majority protein IDs, Gene names, LFQ/iBAQ measurement columns, Reverse, Potential contaminant, Only identified by site. The latter three may be empty.

2. Demo_clinicaldata.txt: The sample description file - a tab separated text file as can be produced with any Office program by saving the spread sheet as .txt. The file needs to contain a column named "PatientID", which matches the sample ID's from the proteinGroups header (without the "LFQ intensity" or "iBAQ" prefixes) and one or more named columns with "parameters", i.e. textual/factual/logical or continuous/integer values. Column names have to be unique.

Access to demo data is possible directly via the upload button if ou are testing on our public server. For your local installation you may directly use your own data or the demo files in Eatomics/Data from the github repository. The demo proteinGroups file represents a shortened version of the data assessed and described in Chen et al. [4] and is accompanied by a sample description file prepared by us, based on the publication's supplementary data.

4. Troubleshooting

• We recommend to use Chrome or Safari as browsers, as we have only thoroughly tested on those two.

• On mac, in order to use the plotly functions, e.g., in the volcano plot, you will have to install Xquartz from https://www.xquartz.org/ and the Cairo package. The error message will contain a hint on the missing Cairo bitmap device.

install.packages("Cairo")
library(Cairo) 

• R version < 3.6 will need a lower version of caTools in order to create proper reports from rmarkdown - this might help to fix any caTools related errors.

install.packages("https://cran.r-project.org/src/contrib/Archive/caTools/caTools_1.14.tar.gz", repos=NULL, type="source")

• if the installation of the rmarkdown or digest package fails an update of packages in general might help

update.packages(ask = FALSE, checkBuilt = TRUE)

• if the online version of the tool seems to be very slow, it might help to disable the websocket protocol for this site in your browser. Within the application, press the keyboard shortcut: Ctrl+Alt+Shift+A (or, from a Mac: control+option+shift+A). This will open a window that will allow you to select or deselect protocols. More info at https://docs.rstudio.com/shiny-server/#disable_protocols.

References

1: Krug, K., et al., A Curated Resource for Phosphosite-specific Signature Analysis. Mol Cell Proteomics, 2019. 18(3): p. 576-593.

2: Ritchie, Matthew E., et al. "limma powers differential expression analyses for RNA-sequencing and microarray studies." Nucleic acids research 43.7 (2015): e47-e47.

3: Lazar, C., "imputeLCMD: a collection of methods for left-censored missing data imputation." R package, version 2 (2015).

4: Chen, Christina Yingxian, et al. "Suppression of detyrosinated microtubules improves cardiomyocyte function in human heart failure." Nature medicine 24.8 (2018): 1225-1233.