This is thedevelopmentversion of DEP; for the stable release version, seeDEP.
Bioconductor version: Development (3.16)
This package provides an integrated analysis workflow for robust and reproducible analysis of mass spectrometry proteomics data for differential protein expression or differential enrichment. It requires tabular input (e.g. txt files) as generated by quantitative analysis softwares of raw mass spectrometry data, such as MaxQuant or IsobarQuant. Functions are provided for data preparation, filtering, variance normalization and imputation of missing values, as well as statistical testing of differentially enriched / expressed proteins. It also includes tools to check intermediate steps in the workflow, such as normalization and missing values imputation. Finally, visualization tools are provided to explore the results, including heatmap, volcano plot and barplot representations. For scientists with limited experience in R, the package also contains wrapper functions that entail the complete analysis workflow and generate a report. Even easier to use are the interactive Shiny apps that are provided by the package.
Author: Arne Smits [cre, aut], Wolfgang Huber [aut]
Maintainer: Arne Smits
Citation (from within R, entercitation("DEP")
):
To install this package, start R (version "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") # The following initializes usage of Bioc devel BiocManager::install(version='devel') BiocManager::install("DEP")
For older versions of R, please refer to the appropriateBioconductor release.
查看文档的版本包age installed in your system, start R and enter:
browseVignettes("DEP")
HTML | R Script | DEP: Introduction |
HTML | R Script | DEP: Missing value handling |
Reference Manual | ||
Text | NEWS |
biocViews | DataRepresentation,DifferentialExpression,ImmunoOncology,MassSpectrometry,Proteomics,Software |
Version | 1.19.0 |
In Bioconductor since | BioC 3.6 (R-3.4) (4.5 years) |
License | Artistic-2.0 |
Depends | R (>= 3.5) |
Imports | ggplot2,dplyr,purrr,readr,tibble,tidyr,SummarizedExperiment(>= 1.11.5),MSnbase,limma,vsn,fdrtool,ggrepel,ComplexHeatmap,RColorBrewer,circlize,shiny,shinydashboard,DT,rmarkdown,assertthat,gridExtra, grid, stats,imputeLCMD,cluster |
LinkingTo | |
Suggests | testthat,enrichR,knitr,BiocStyle |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | proDA,RforProteomics |
Links To Me | |
Build Report |
Followbob 体育网址 instructions to use this package in your R session.
Source Package | DEP_1.19.0.tar.gz |
Windows Binary | DEP_1.19.0.zip(64-bit only) |
macOS 10.13 (High Sierra) | DEP_1.19.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/DEP |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/DEP |
Package Short Url | //www.anjoumacpherson.com/packages/DEP/ |
Package Downloads Report | Download Stats |
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