There are 8 repositories under proteomics-data-analysis topic.
Olink R package: A collection of functions to facilitate analysis of proteomic data from Olink. The goal of this package is to help users extract biological insights from proteomic data run on the Olink platform.
The SomaDataIO package loads and exports 'SomaScan' data via the 'SomaLogic Operating Co., Inc.' proprietary data file, called an ADAT ('*.adat'). The package also exports auxiliary functions for manipulating, wrangling, and extracting relevant information from an ADAT object once in memory.
An modular and extensible app for visualization of mass spectrometry data and optimization of data acquisition.
amica: an interactive and user-friendly web-based platform for the analysis of proteomics data
`sdrf-pipelines` is the official SDRF file validator and converts SDRF to pipeline configuration files
Shiny app for making and annotating Volcano plots
HistoJS: Web-Based Analytical Tool for Multiplexed Images. Limited Github Online Demo 👇
CLI toolkit for fast analysis of DIA proteomics experiments and in silico library prediction
Multiplexed data-independent acquisition (plexDIA) for increasing proteomics throughput. The code is distributed by an MIT license.
Initial recommendations for performing, benchmarking, and reporting single-cell proteomics experiments. The code is distributed under an MIT license.
autoprot provides standardised, fast, and reliable proteomics data analysis while ensuring a high customisability needed to tailor the analysis pipeline to specific experimental strategies.
This repository contains the code to reproduce our exploratory analysis of a pan-cancer plasma proteomics dataset, including differential expression analysis and disease classification (https://doi.org/10.1038/s41467-023-39765-y). The data can be explored in the Human Protein Atlas: www.proteinatlas.org/humanproteome/disease.
A resource for biomedical students and researchers. Includes proteomics software tools like FragPipe, MaxQuant, PDV, SearchGUI, ThermoRawFileParser, and PeptideShaker. Offers a user-friendly interface, automated identification and quantification, comprehensive data analysis, and lightweight clone feature for optimized storage.
MaxQuant and Perseus Bug Reporting
Python framework for explainable omics analysis
Visualization of spectral archive
QuantQC is a package for quality control (QC) of single-cell proteomics data. It is optimized to work with nPOP, a method for massively parallel sample preparation on glass slides.
R script to perform standard analysis steps for label-free proteomics data
An R package providing extended biological annotations for the SomaScan Assay, a proteomics platform developed by SomaLogic Operating Co., Inc.
Code accompanying batch effects processing workflow for "omic" data, mainly targeted for proteomics
GRaph-based Analysis of Subcellular/Spatial Proteomics
📊 User-friendly mass spectrometry and chromatography data analysis app with native UI, graphing, quantification, MS/MS and data export capabilities
Inspecting the quality of isobaric labeling proteomic data in a Jupyter notebook. Data output from Proteome Discoverer.
Annotation and processing of peptides from FragPipe search results
Protein Cleaver is a versatile tool for protein analysis and digestion.
WeSA (Weighted SocioAffinity): a tool for improving affinity proteomics data.
Cell Permeability analysis
HIquant: An algorithm for quantifying homologous proteins and proteoforms from bottom-up mass-spec data
A highly specialized suite of standardized plotting routines based on the "Grammar of Graphics" framework of mapping variables to aesthetics used in 'ggplot2'. Graphics types are biased towards visualizing SomaScan (proteomic) data.
Code of the R Shiny App of the PRONE R Package.
Map residue numbers from experimental protein structures to primary protein sequences and calculate the relative solvent accessibility of each residue
Identify small-molecule sites of labeling that are annotated as active sites, binding sites, disulfide bonds and redox active sites
R package and Shiny app for the dowstream analysis of quantitative proteomic data
Analysis from Leduc and Slavov (2025): Protein degradation and growth dependent dilution substantially shape mammalian proteomes
Automated parser for VaxiJen output 🚀 A lightweight Perl tool to extract and tabulate antigenicity predictions from VaxiJen . Designed for bioinformatics, immunoinformatics, and reverse vaccinology workflows, this script helps researchers process large datasets into clean, ready-to-analyze tables.