This program is developed based on the Shiny framework, a set of R packages and a collection of scripts written by members of Junhyong Kim Lab at University of Pennsylvania. Its goal is to facilitate fast and interactive RNA-Seq data analysis and visualization. Current version of PIVOT supports routine RNA-Seq data analysis including normalization, differential expression analysis, dimension reduction, correlation analysis, clustering and classification. Users can complete workflows of DESeq2, monocle and scde package with just a few button clicks. All analysis reports can be exported, and the program state can be saved, loaded and shared.
PIVOT is installable as a regular R package or a (currently) community-developed Docker image
# Dependecies that needs to be manually installed.
# You may need to paste the following code line by line
# and choose if previously installed packages should be updated (recommended).
install.packages("devtools")
library("devtools")
install.packages("BiocManager")
BiocManager::install("BiocUpgrade")
BiocManager::install("GO.db")
BiocManager::install("HSMMSingleCell")
BiocManager::install("org.Mm.eg.db")
BiocManager::install("org.Hs.eg.db")
BiocManager::install("DESeq2")
BiocManager::install("SingleCellExperiment")
BiocManager::install("scater")
BiocManager::install("monocle")
BiocManager::install("GenomeInfoDb")
# Install PIVOT
install_github("qinzhu/PIVOT")
BiocManager::install("BiocGenerics") # You need the latest BiocGenerics >=0.23.3
devtools::install_version("shiny", version = "1.3.0", repos = "http://cran.us.r-project.org") # Latest shiny 1.4.0 has bug in module reactivity
library(PIVOT)
pivot()
PIVOT can be launched (and installed/updated if needed) using a single command:
docker pull eturkes/pivot-docker && docker run -p 80:3838 eturkes/pivot-docker
Listening on http://0.0.0.0:3838
in the terminal window.localhost
.Ctrl+C
into its terminal window. Note that the PIVOT state will NOT be saved, one must use the "Save State" feature within "System Control" (section 17 of the PIVOT manual) if they would like to do so.See here: https://rawgit.com/qinzhu/PIVOT/master/inst/app/www/manual_file.html
Or download: https://kim.bio.upenn.edu/software/pivot/manual_file.html.zip
URL 'http://xxx.tgz': status was '404 Not Found'
chooseCRANmirror()
to select another CRAN mirror."Maximum DLL loaded error". Unfortunately current R only permits maximum of 100 loaded DLLs. This issue will be fixed with the release of the developmental version of R (See https://stackoverflow.com/questions/36974206/error-maximal-number-of-dlls-reached).
For now, we suggest only load necessary modules when launching PIVOT. If your analysis require entire workflow, consider adding the environmental variable "R_MAX_NUM_DLLS=150" to .Renviron file located at "/Library/Frameworks/R.framework/Resources/etc"(MacOs); or .bash_profile with "export R_MAX_NUM_DLLS=150" (Linux).
'SingleCellExperiment' package cannot be correctly installed
BiocManager::install("BiocUpgrade")
BiocManager::install("SingleCellExperiment")
If you ran into any problems like 'SingleCellExperiment','SCESet' or 'pData', its likely that you have old scater installed. The new scater package changes all the grammar so you need to first remove the old package by calling remove.packages("scater")
and reinstall the latest version by using BiocManager::install("scater")
.
Dependency openssl configuration failed
brew install openssl
. Then try install PIVOT again.MacOS specific: you might need to install xcode developer tools if you encounter installation error such as 'missing xcrun'.
To install, Open Terminal, and run the following:
xcode-select --install
BiocManager::install
if it is from BioConductor or install.packages()
if it is CRAN (if you are unsure, try one and if it fails, try the other). Some users found this was necessary for the BioConductor packages GenomicAlignments
and rtracklayer
. If the package still fails to install, you can try binaries from BioConductor/CRAN or package manager if on Linux. Some users found this was necessary for the CRAN package nloptr
.Zhu, Q., Fisher, S. A., Dueck, H., Middleton, S., Khaladkar, M., & Kim, J. (2018). PIVOT: platform for interactive analysis and visualization of transcriptomics data. BMC bioinformatics, 19(1), 6.
For specific analysis, please check the citation listed in the module.
Qin Zhu
Junhyong Kim Lab
University of Pennsylvania
2015 - 2017