PhycoMine

PhycoMine integrates and analyzes genomic, transcriptomic, proteomic, and phenotypic datasets from microalgae to support comparative genomics, gene expression profiling, metabolic pathway analysis, and phenotype–genotype investigations.

Key Features:

• Integrated Data Analysis: Consolidates genomic, transcriptomic (RNA-seq), proteomic, and phenotypic datasets for microalgae into a unified extended database model.
• Chromosome Distribution Analysis: Provides analysis of chromosome distribution and genomic feature localization.
• Gene Expression and Transcriptomics: Quantifies and compares gene expression using RNA-seq data from public repositories and internally reanalyzed datasets.
• Proteomics Set Analysis: Supports integration and set-based analysis of proteomics datasets.
• Enrichment Analyses: Performs Gene Ontology (GO), KEGG pathway, EggNOG, transcription factor and regulator enrichment, and publication enrichment analyses.
• Phenotypic Data Visualization: Links phenotypic data to molecular datasets and provides visualization of phenotype-associated patterns.
• Comparative Analysis: Incorporates a reanalysis of 200 RNA-seq datasets from Chlamydomonas reinhardtii to enhance comparative and cross-experiment analyses.
• Metabolic Pathway and Network Analysis: Maps selected genes and proteins to metabolic pathways and supports biological network analysis.
• Orthologue Gene Analysis: Enables identification and analysis of orthologous genes across species for evolutionary and functional inference.

Scientific Applications:

• Gene expression analysis: Differential and comparative analysis of gene expression across experiments and conditions using RNA‑seq data.
• Pathway elucidation: Mapping of genes and proteins to KEGG pathways and metabolic networks to clarify biochemical pathways.
• Comparative genomics and orthology: Cross-species comparisons and orthologue analysis, including datasets from Chlamydomonas reinhardtii.
• Functional enrichment and annotation: Functional interpretation via GO, EggNOG, transcription factor/regulator, and publication enrichment analyses.
• Phenotype–genotype association: Investigation of relationships between molecular datasets and phenotypic traits.

Methodology:

Implemented on the InterMine software framework with an extended database model to support complex queries and integrated management of genomic, transcriptomic (RNA‑seq), proteomic, and phenotypic data; includes a reanalysis of 200 Chlamydomonas reinhardtii RNA-seq datasets and provides simultaneous querying across multiple datasets along with visualization options.