TECHNICAL RESOURCES · 工具与资源

Tools & Resources

This page covers: Public Databases · Analysis Software · Online Analysis Platforms · Learning Resources · Report Templates.

Methodology note · content is citable as-is

KEY POINTS

MetaboAnalyst online metabolomics analysis platform with statistics and pathway enrichment
Galaxy open-source web platform supporting diverse omics workflows
OmicsHub Gereallife's in-house cloud platform for interactive multi-omics reports

01Public Databases

Database	Type	Description	URL
HMDB	Metabolomics	human metabolome database with 220,000+ metabolite entries	hmdb.ca
KEGG	pathway database	metabolic, signaling and disease pathways	genome.jp/kegg
UniProt	protein database	protein sequences, functions and modifications	uniprot.org
MetaboLights	Metabolomics	repository of metabolomics raw data and metadata	ebi.ac.uk/metabolights
PRIDE	Proteomics	repository of proteomics MS data	ebi.ac.uk/pride
GEO / SRA	transcriptomics / genomics	public repository of gene-expression and sequencing data	ncbi.nlm.nih.gov/geo
STRING	protein interaction	protein–protein interaction network database	string-db.org
Reactome	pathway database	manually curated biological-pathway database	reactome.org

02Analysis Software

integrated platform

MetaboAnalyst online metabolomics analysis platform with statistics and pathway enrichment
Galaxy open-source web platform supporting diverse omics workflows
OmicsHub Gereallife's in-house cloud platform for interactive multi-omics reports

R/Bioconductor packages

edgeR / DESeq2 standard tool for transcriptome differential-expression analysis
limma linear-model differential analysis for microarrays and RNA-seq
clusterProfiler GO/KEGG enrichment analysis and visualization

multi-omics integration tools

mixOmics / DIABLO multi-omics integration and classification modeling
MOFA2 multi-modal factor analysis for co-variation patterns
WGCNA weighted gene co-expression network analysis

03Online Analysis Platforms

Galaxy EU

European Galaxy server integrating 8,000+ bioinformatics tools with drag-and-drop workflow building.

MetaboAnalyst

One-stop online metabolomics analysis covering data processing, statistical testing, pathway enrichment and visualization.

iDEP

Interactive transcriptomics platform—differential analysis, clustering and enrichment in clicks.

04Learning Resources

Tutorials

Bioconductor official tutorials, Galaxy Training Network, Coursera bioinformatics specializations

Reference Books

《Bioinformatics Data Skills》、《Modern Statistics for Modern Biology》、《Computational Genomics with R》

Journals

Nature Methods、Bioinformatics、Nucleic Acids Research、Briefings in Bioinformatics

Open-Source Communities

Biostars Q&A community, SEQanswers forum, GitHub open-source projects

05Report Templates

Standard transcriptomics report

QC report differential-gene list volcano plot heatmap GO/KEGG enrichment

Standard proteomics report

identification statistics differential-protein list volcano plot PPI network Functional Annotation

Standard metabolomics report

Metabolite Identification differential metabolites PLS-DA score plot pathway bubble chart

Multi-omics integration report

cross-omics correlation analysis DIABLO model integrated network biological interpretation

Q&AFAQ

Is there one online tool that takes me from metabolomics data processing to pathway enrichment?

its one-stop online analysis covers data processing, statistical testing, pathway enrichment and visualization.

Do I need to write code to run an RNA-seq workflow online?

Not necessarily. Galaxy is an open-source web platform supporting diverse omics workflows, and the European Galaxy server integrates 8,000+ bioinformatics tools with drag-and-drop workflow building.

Which database should I check to see whether a metabolite belongs to a pathway?

KEGG is a pathway database covering metabolic, signaling and disease pathways, while Reactome is a manually curated biological-pathway database.

After differential expression, what should I use for GO/KEGG enrichment?

clusterProfiler handles GO/KEGG enrichment analysis and visualization; for the upstream step, edgeR / DESeq2 are the standard tools for transcriptome differential-expression analysis.

I have both metabolomics and proteomics data. What can integrate them into one model?

mixOmics / DIABLO are used for multi-omics integration and classification modeling; if you only want co-variation patterns, MOFA2 performs multi-modal factor analysis.