How does this skill handle reproducibility?

It provides a Snakemake pipeline pattern that orchestrates the entire analysis from raw data loading to final HTML report generation, ensuring consistent and reproducible results.

Does this skill support different mass spectrometry search engines?

Yes, it includes patterns for reading and preprocessing data from common search engines including Spectronaut BGS, FragPipe, and MaxQuant using the prolfquappPTMreaders library.

What is the difference between DPA and DPU in this skill?

DPA (Differential PTM Abundance) measures raw signal changes of phosphosites, whereas DPU (Differential PTM Usage) normalizes those changes against the total protein abundance to identify changes in modification stoichiometry.

Can I use this for non-human species like mouse models?

Absolutely. The skill provides specific logic for mouse-to-human ortholog mapping via biomaRt and uses flanking-sequence-based PTM-SEA, which is species-invariant.

Phosphoproteomics PTM Analysis

Name: Phosphoproteomics PTM Analysis
Author: CodingKaiser

byCodingKaiser

データサイエンスとML

Analyzes phosphoproteomics data using R to identify differential post-translational modification abundance, stoichiometry, and kinase activity.

概要

This skill provides specialized guidance for bioinformaticians and researchers conducting phosphoproteomics analysis within the R ecosystem. It offers structured patterns for Differential PTM Abundance (DPA), protein-normalized Differential PTM Usage (DPU), and Kinase-Substrate Enrichment Analysis (KSEA). By leveraging the prolfqua and prophosqua packages, it helps users transform search engine outputs from Spectronaut, FragPipe, or MaxQuant into statistically rigorous insights, complete with mouse-to-human ortholog mapping, PTM-SEA signatures, and reproducible Snakemake pipeline architectures.

主な機能

Implements Kinase-Substrate Enrichment Analysis (KSEA) and species-invariant PTM-SEA using flanking sequences.
0 GitHub stars
Provides pre-built R patterns for data normalization, missing value handling, and site-centric aggregation.
Generates publication-quality visualizations including sequence logos, complex heatmaps, and enrichment plots.
Calculates Differential PTM Abundance (DPA) and protein-normalized usage (DPU) via linear modeling.
Integrates with Snakemake for reproducible end-to-end omics workflow orchestration.

ユースケース

Automating large-scale omics reporting using parameterized RMarkdown and Parquet-based data storage.
Mapping mouse phosphoproteomics data to human orthologs for kinase activity inference and cross-species comparison.
Normalizing phosphorylation site data against total protein levels to reveal true stoichiometric changes.

概要

主な機能

Implements Kinase-Substrate Enrichment Analysis (KSEA) and species-invariant PTM-SEA using flanking sequences.
0 GitHub stars
Provides pre-built R patterns for data normalization, missing value handling, and site-centric aggregation.
Generates publication-quality visualizations including sequence logos, complex heatmaps, and enrichment plots.
Calculates Differential PTM Abundance (DPA) and protein-normalized usage (DPU) via linear modeling.
Integrates with Snakemake for reproducible end-to-end omics workflow orchestration.

ユースケース

Automating large-scale omics reporting using parameterized RMarkdown and Parquet-based data storage.
Mapping mouse phosphoproteomics data to human orthologs for kinase activity inference and cross-species comparison.
Normalizing phosphorylation site data against total protein levels to reveal true stoichiometric changes.