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This repository contains the source code and datasets used to reproduce the results from the manuscript:
“Multi-Omics Meta-Analysis Provides Insights into Reversible Phosphorylation During Arabidopsis Skotomorphogenesis.”


Description

The project includes a C# program and a set of R scripts designed for multi-omics data integration and analysis.
Data from transcriptomic, proteomic, and phosphoproteomic experiments are organized in an SQLite database for convenience.


Features

Implemented in C#

  • Data integration: Aggregates data in an SQLite relational database.
  • Dataset management: Supports multiple genome annotations and RNAseq, proteomic, and phosphoproteomic datasets that can be grouped into independent pools (experimental conditions).
  • Genome annotation: Loads .GFF and .fasta files to import gene models and sequences.
  • Protein translation: Translates CDS annotations into protein sequences, which can be exported as .fasta files.
  • GO annotations: Loads GO term relationships and annotations. The list of genes annotated with any GO term ID can be retrieved.
  • Transcriptomic data: Loads expression matrices (gene IDs with read counts, RPKM, or TPM values) and handles multiple experiments and replicates.
  • Proteomic data: When peptide sequences are provided, exact sequence matching is performed against protein sequences; otherwise, mapping is based on gene IDs.
  • Phosphoproteomic data: Supports different formats for specifying residue positions.
  • External tool outputs: Accumulates outputs from ScanProSite, PrDOS, and TMHMM.
  • Regex matching: Performs regular expression searches in protein sequences (e.g., to identify kinase recognition motifs).

Implemented in R

  • Data normalization: Performs linear regressions to standardize and average transcript and protein abundance values across datasets.
  • Visualization: Generates scatter plots, density plots, heatmaps, and protein domain diagrams with phosphorylation sites using ggplot2.
  • Phylogenetic analysis: Visualizes phylogenetic trees (from .nwk files) using ggtree.

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