proBatch

Tools for Batch Effects Diagnostics and Correction

https://github.com/symbioticme/probatch

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
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  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
    2 of 7 committers (28.6%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (13.6%) to scientific vocabulary

Keywords

batch-effects normalization proteome
Last synced: 6 months ago · JSON representation

Repository

Tools for Batch Effects Diagnostics and Correction

Basic Info
  • Host: GitHub
  • Owner: symbioticMe
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 4.8 MB
Statistics
  • Stars: 16
  • Watchers: 4
  • Forks: 6
  • Open Issues: 6
  • Releases: 0
Topics
batch-effects normalization proteome
Created about 8 years ago · Last pushed 10 months ago
Metadata Files
Readme

README.md

proBatch

<!-- badges: start --> Lifecycle: maturing BioC status License: GPL v3

Build Status

General Overview

The proBatch package facilitates batch effects analysis and correction high-throughput experiments. Although the package has primarily been developed for DIA (SWATH) proteomics data, it should also be applicable to most omic data with minor adaptations.

The package contains functions for diagnostics (proteome/genome-wide and feature-level), correction (normalization and batch effects correction) and quality control.

Diagnostics part of the package features unified color scheme for plotting, that allows to produce publication-quality graphs.

Correction functions are convenient wrappers for common normalization and batch effects removal approaches such as quantile normalization and median centering. Furthermore, the package includes non-linear fitting based approaches to deal with complex, mass spectrometry-specific signal drifts.

Quality control step, mostly based on correlation analysis, allows to assess whether the correction improved the quality of the data.

All steps of batch effects analysis and correction are illustrated in the vignette, using the subset of real-world large-scale dataset.

Please use following manuscript for citation: Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial. Molecular Systems Biology 17, e10240 (2021).

Installing

Install the dependencies:

``` biocdeps <- c("GO.db", "impute", "preprocessCore", "pvca","sva" ) crandeps <- c("corrplot", "data.table", "ggplot2", "ggfortify","lazyeval", "pheatmap", "reshape2", "rlang", "tibble", "dplyr", "tidyr", "wesanderson","WGCNA")

if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install(biocdeps) install.packages(crandeps) ```

NOTE: You might need to also install the following linux packages: apt-get install libxml2-dev libz-dev

Optionally also install:

install.packages(c("devtools", "roxygen2", "testthat"))

Install proBatch from github:

library(devtools) install_github("symbioticMe/proBatch", build_vignettes = TRUE)

Exploring the package

The complete documentation: help(proBatch)

Browse the vignette: browseVignettes('proBatch')

Citation

Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial. Molecular Systems Biology 17, e10240 (2021). https://doi.org/10.15252/msb.202110240

Owner

  • Name: Jelena Čuklina
  • Login: symbioticMe
  • Kind: user

GitHub Events

Total
  • Watch event: 1
  • Member event: 2
  • Issue comment event: 4
  • Push event: 1
  • Pull request event: 2
Last Year
  • Watch event: 1
  • Member event: 2
  • Issue comment event: 4
  • Push event: 1
  • Pull request event: 2

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 9,328
  • Total Committers: 7
  • Avg Commits per committer: 1,332.571
  • Development Distribution Score (DDS): 0.479
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Jelena Chuklina c****a@g****m 4,857
Chloe H. Lee h****b@g****m 3,965
ppatrick p****i@g****m 432
Lee Chloe l****h@e****h 64
Chloe H. Lee 4****J 4
Nitesh Turaga n****a@g****m 4
Mikolaj Rybinski m****i@i****h 2
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 5,930 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
bioconductor.org: proBatch

Tools for Diagnostics and Corrections of Batch Effects in Proteomics

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 5,930 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Average: 22.8%
Downloads: 68.4%
Maintainers (1)
Last synced: 10 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.6 depends
  • Biobase * imports
  • RColorBrewer * imports
  • WGCNA * imports
  • corrplot * imports
  • data.table * imports
  • dplyr * imports
  • ggfortify * imports
  • ggplot2 * imports
  • grDevices * imports
  • lazyeval * imports
  • lubridate * imports
  • magrittr * imports
  • pheatmap * imports
  • preprocessCore * imports
  • purrr * imports
  • pvca * imports
  • reshape2 * imports
  • rlang * imports
  • scales * imports
  • stats * imports
  • sva * imports
  • tibble * imports
  • tidyr * imports
  • tools * imports
  • utils * imports
  • viridis * imports
  • wesanderson * imports
  • devtools * suggests
  • ggpubr * suggests
  • gridExtra * suggests
  • gtable * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • roxygen2 * suggests
  • spelling * suggests
  • testthat >= 2.1.0 suggests